{"access":{"advertiser_pricing_url":"https://aidevboard.com/pricing","catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. API keys are optional for stable agent identity and keyed hourly throttling.","docs_url":"https://aidevboard.com/docs","mode":"open","register_url":"https://aidevboard.com/api/v1/register"},"degraded":false,"estimated":false,"has_next":true,"jobs":[{"id":"48720738-0f4b-483d-9739-14039ae457d0","company_id":"a0000000-0000-0000-0000-000000000001","title":"Research Engineer, Performance RL (Reinforcement Learning) ","slug":"research-engineer-performance-rl-2f0da25a","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the RL Teams \n Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Sonnet 4.6 and Opus 4.6. Our work spans several key areas:\n \n \n Developing systems that enable models to use computers effectively\n \n Advancing code generation through reinforcement learning\n \n Pioneering fundamental RL research for large language models\n \n Building scalable RL infrastructure and training methodologies\n \n Enhancing model reasoning capabilities\n \n We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish.\n About the Role \n We're hiring for the Code RL team within the RL organization. As a Research Engineer, you'll advance our models' ability to safely write correct, fast code for accelerators.\n You'll need to know accelerator performance well to turn it into tasks and signals models can learn from. Specifically, you will:\n \n \n Invent, design and implement RL environments and evaluations.\n \n Conduct experiments and shape our research roadmap.\n \n Deliver your work into training runs.\n \n Collaborate with other researchers, engineers, and performance engineering specialists across and outside Anthropic.\n \n You may be a good fit if you:\n \n \n Have expertise with accelerators (CUDA, ROCm, Triton, Pallas), ML framework programming (JAX or PyTorch).\n \n Have worked across the stack – kernels, model code, distributed systems.\n \n Know how to balance research exploration with engineering implementation.\n \n Are passionate about AI's potential and committed to developing safe and beneficial systems.\n \n Strong candidates may also have:\n \n \n Experience with reinforcement learning.\n \n Experience porting ML workloads between different types of accelerators.\n \n Familiarity with LLM training methodologies.\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $350,000 — $850,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a ","salary_min":350000,"salary_max":850000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["gpu","alignment","search","jax","distributed-systems","code-generation","pytorch","llm"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5160330008","is_featured":true,"is_sticky":true,"status":"active","published_at":"2026-03-23T16:27:59Z","expires_at":"2026-08-14T14:00:28.788703Z","created_at":"2026-04-13T09:36:00.086246Z","updated_at":"2026-07-15T14:00:28.927351Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/48720738-0f4b-483d-9739-14039ae457d0"},{"id":"f8c6c621-b459-40f6-b41d-0baa191734ff","company_id":"a0000000-0000-0000-0000-000000000001","title":"Research Lead, Training Insights","slug":"research-lead-training-insights-6091f430","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role \n As a Research Lead on the Training Insights team, you'll develop the strategy for, and lead execution on, how we measure and characterize model capabilities across training and deployment. This is a hands-on leadership role: you'll drive original research into new evaluation methodologies while leading a small team of researchers and research engineers doing the same.\n Your work will span the full lifecycle of model development. You'll research and build new long-horizon evaluations that test the boundaries of what our models can achieve, develop novel approaches to measuring emerging capabilities, and deepen our understanding of how those capabilities develop — both during production RL training and after. You'll also take a cross-organizational view, working across Reinforcement Learning, Pretraining, Inference, Product, Alignment, Safeguards, and other teams to map the landscape of model evaluations at Anthropic and identify critical gaps in coverage.\n This role carries significant visibility and impact. You'll help shape the evaluation narrative for model releases, contributing directly to how Anthropic communicates about its models to both internal and external audiences. Done well, you will change how the industry measures and understands model capabilities, significantly furthering our safety mission.  \n Responsibilities:  \n \n Build new novel and long-horizon evaluations\n Develop novel measurement approaches for understanding how model capabilities emerge and evolve during RL training\n Lead strategic evaluation coverage across the company\n Shape the evaluation narrative for model releases\n Lead and mentor a small team of researchers and research engineers, setting research direction and fostering a culture of rigorous, creative research\n Design evaluation frameworks that balance scientific rigor with the practical demands of production training schedules\n Build and maintain relationships across Anthropic's research organization to ensure evaluation insights inform training and deployment decisions\n Contribute to the broader research community through publications, open-source contributions, or external engagement on evaluation best practices\n \n You may be a good fit if you:  \n \n Have significant experience designing and running evaluations for large language models or similar complex ML systems\n Have led technical projects or teams, either formally or through sustained ownership of critical research directions\n Are equally comfortable designing experiments and writing code—you can move between research and implementation fluidly\n Think strategically about what to measure and why, not just how to measure it\n Can synthesize information across multiple teams and workstreams to form a coherent picture of model capabilities\n Communicate complex technical findings clearly to both technical and non-technical audiences\n Are results-oriented and thrive in fast-paced environments where priorities shift based on research findings\n Care deeply about AI safety and want your work to directly influence how capable AI systems are developed and deployed\n \n Strong candidates may also have:  \n \n Experience building evaluations for long-horizon or agentic tasks\n Deep familiarity with Reinforcement Learning training dynamics and how model behavior changes during training\n Published research in machine learning evaluation, benchmarking, or related areas\n Experience with safety evaluation frameworks and red teaming methodologies\n Background in psychometrics, experimental psychology, or other measurement-focused disciplines\n A track record of communicating evaluation results to inform high-stakes decisions about model development or deployment\n Experience managing or mentoring researchers and engineers\n \n Representative projects:  \n \n Designing and implementing a suite of long-horizon evaluations that test model capabilities on tasks requiring sustained reasoning, planning, and tool use over extended interactions\n Building systems to track capability development across RL training checkpoints, surfacing insights about when and how specific capabilities emerge\n Conducting a cross-org audit of evaluation coverage, identifying blind spots, and prioritizing new evaluations to fill critical gaps across Pretraining, RL, Inference, and Product\n Developing the evaluation methodology and narrative for a major model release, working with research leads and communications to clearly characterize model capabilities and limitations\n Researching and prototyping novel evaluation approaches for capabilities that are difficult to measure with existing benchmarks\n Leading a team","salary_min":850000,"salary_max":850000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["agents","llm","alignment","reinforcement-learning","pre-training","search","research"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5139654008","is_featured":true,"is_sticky":false,"status":"active","published_at":"2026-03-06T17:15:29Z","expires_at":"2026-08-14T14:00:30.363031Z","created_at":"2026-04-13T09:36:01.625992Z","updated_at":"2026-07-15T14:00:30.486844Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f8c6c621-b459-40f6-b41d-0baa191734ff"},{"id":"be679834-9c8e-4780-bdad-f2d02b24a22e","company_id":"a0000000-0000-0000-0000-000000000001","title":"Safeguards Enforcement Analyst, Violence \u0026 Extremism","slug":"safeguards-enforcement-analyst-violence-extremism-5a4dffe7","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role \n As a Safeguards Enforcement Analyst focused on Violence \u0026 Extremism, you will be responsible for building and executing operational workflows to assess model behavior, drive enforcement decisions, and develop evals across a technically demanding range of policy areas. Your work spans detecting and mitigating attempts to misuse Anthropic's AI systems to facilitate real-world harm, including weapons and dangerous technology, critical infrastructure attacks, violent extremism, and threats of violence.\n Important context for this role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a violent, graphic, hateful, or psychologically disturbing nature.\n Key responsibilities \n \n Design and architect automated enforcement systems and review workflows that scale effectively while maintaining high accuracy\n Develop and maintain evals that measure model performance on these policy areas, surface regressions, and inform policy and model improvements\n Partner with Engineering and Data Science to optimize detection and automated enforcement systems for potential policy violations\n Review flagged content to drive enforcement decisions and surface policy gaps, with particular attention to novel or technically sophisticated misuse attempts + emerging extremist movements, ideologies, and mobilization tactics\n Support the Safeguards policy design team by providing structured feedback on policy gaps and enforcement ambiguities based on real enforcement scenarios\n Develop and maintain enforcement guidelines and reviewer documentation that enable accurate, consistent enforcement across a wide range of content\n Keep up to date with emerging threats, terrorist and extremist movements, regulatory changes, and AI policy enforcement best practices, and apply these to inform our workflows and evals\n Identify and escalate emerging misuse patterns, novel attack vectors, and signs of coordinated violent extremist activity\n \n Minimum qualifications \n \n Experience in policy enforcement, threat intelligence, counterterrorism, government, or a closely related field, with direct exposure to harmful content, dangerous technology, violent extremism, or physical harm facilitation\n Experience standing up and scaling policy enforcement or content review workflows\n Proficiency in SQL and/or other data analysis tools to draw insights from large datasets and monitor enforcement workflow health\n Experience identifying emerging risks and threat actors, and communicating findings to a diverse set of stakeholders, such as Product, Policy, Engineering, and Legal teams\n Experience working with generative AI products, including writing effective prompts for content review and enforcement\n Understanding of the challenges involved in implementing product policies at scale, including in the content moderation space\n \n Preferred qualifications \n \n Subject matter expertise in one or more high-stakes harm areas, such as weapons and dangerous technology, violent extremism, terrorism, autonomous systems, or critical infrastructure protection\n Familiarity with relevant legal and regulatory frameworks governing dangerous technology, critical infrastructure, or domestic/international terrorism\n Experience developing evals or red-teaming AI systems, particularly for harmful content or policy enforcement use cases\n Experience with threat actor profiling and threat intelligence frameworks (e.g., MITRE ATT\u0026CK)\n Experience tracking threat actors, extremist networks, or misuse patterns across surface, deep, and dark web environments\n Experience with large language models and an understanding of how AI technology could provide meaningful uplift toward serious harm\n Proficiency in Python for data analysis and workflow automation\n Background in law enforcement, national security, defense, counterterrorism, or a relevant regulatory environment\n Experience assessing the technical plausibility and real-world harm potential of content, including the ability to distinguish between general educational content and genuine operational uplift, and between protected speech and genuine incitement/mobilization\n Familiarity with cross-platform threat analysis and OSINT techniques\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $285,000 — $330,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of ","salary_min":285000,"salary_max":330000,"location":"New York, NY","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","generative-ai","alignment","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5343907008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-15T00:47:43Z","expires_at":"2026-08-14T14:00:32.214041Z","created_at":"2026-07-15T14:00:32.344861Z","updated_at":"2026-07-15T14:00:32.344861Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/be679834-9c8e-4780-bdad-f2d02b24a22e"},{"id":"45810c38-51f8-47ab-83a8-b91cb2515162","company_id":"a0000000-0000-0000-0000-000000000001","title":"Safeguards Enforcement Analyst, Fraud \u0026 Scams","slug":"safeguards-enforcement-analyst-fraud-scams-028dd4c2","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role\n As a Safeguards Enforcement Analyst on the account abuse team, you'll build and execute enforcement workflows that keep our products safe, with a focus on detecting and mitigating potential harm. Your initial focus will be standing up fraud \u0026 scams enforcement as a program: today this work is handled reactively and in fragments — payment fraud, promotional abuse, and scam-pattern enforcement don't yet have a single owner. You'll be that owner: defining the policy area, building the detection-to-enforcement pipeline, and setting the operating model that a contractor bench can execute against. The surface area is broad: payment fraud (stolen cards, chargebacks, disputes), promotional and credits abuse, and the use of accounts to run scams against third parties.\n This position may expand into broader areas of enforcement over time. Safety is core to our mission, and you'll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way.\n Key responsibilities \n \n Define the fraud \u0026 scams policy taxonomy and how cases are classified, prioritized, and escalated\n Investigate and dismantle organized abuse rings, converting findings into durable controls\n Stand up proactive fraud detection and customer-facing communication flows for fraudulent organization cases\n Build the dispute and chargeback strategy in partnership with payments and card-network partners\n Quantify fraud losses and control efficacy to drive investment decisions\n Author the contractor playbook for fraud review and own QA of scaled output\n Keep up to date with emerging AI policy enforcement best practices, and use these to inform our decision-making and workflows\n \n Minimum qualifications\n \n Deep payment-fraud experience at a fintech, marketplace, or platform — chargebacks, disputes, card-testing, promotional abuse\n Experience building or significantly scaling a fraud program from an early state, not just operating a mature one\n A working command of payment-network and dispute mechanics, sufficient to make strategy calls on them\n Comfort being the sole owner of an area: prioritizing ruthlessly, shipping iteratively, and asking for help precisely\n Comfort using data (SQL or similar tools) to quantify fraud losses and control efficacy\n Strong written communication skills, with experience producing clear briefs and recommendations for technical and non-technical stakeholders\n Excellent judgment and the ability to collaborate with team members while navigating rapidly evolving priorities and workstreams\n \n Preferred qualifications\n \n Experience working directly with payment service providers and card networks on fraud strategy\n Experience with scam typologies beyond payments — social engineering, impersonation, platform-mediated scams\n Experience managing vendor relationships in the fraud/risk detection space\n A deep interest in AI safety and responsible technology development\n Experience writing effective prompts for generative AI systems in a content review or enforcement context\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $245,000 — $285,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application ","salary_min":245000,"salary_max":285000,"location":"New York, NY","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["alignment","generative-ai","payments","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5319554008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-14T03:10:05Z","expires_at":"2026-08-14T14:00:31.784066Z","created_at":"2026-07-15T14:00:31.991198Z","updated_at":"2026-07-15T14:00:31.991198Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/45810c38-51f8-47ab-83a8-b91cb2515162"},{"id":"6fc9c11a-5817-4f35-acb7-d96f007c4325","company_id":"a0000000-0000-0000-0000-000000000001","title":"Safeguards Enforcement Analyst, Ban Evasion \u0026 Recidivism","slug":"safeguards-enforcement-analyst-ban-evasion-recidivism-2b8cbefe","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role \n As a Safeguards Enforcement Analyst on the account abuse team, you'll build and execute enforcement workflows that keep our products safe, with a focus on detecting and mitigating potential harm. Your initial focus will be recidivism: a ban that an actor can evade in five minutes isn't enforcement — it's friction. You'll own detecting when banned actors return, linking accounts across identities, and closing the re-registration paths that matter most. The mandate includes our highest-stakes populations, including preventing evasion of child-safety enforcement bans, where the cost of a missed return is unacceptable.\n This position may expand into broader areas of enforcement over time. Safety is core to our mission, and you'll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way.\n Key responsibilities \n \n Investigate evasion clusters end to end — from a single appeal or signal anomaly to the full linked actor network\n Convert individual findings into durable systemic controls and detection proposals\n Operationalize re-registration controls for high-severity ban populations\n Partner with Engineering and Data Science teams on account-linking signals to connect returning actors across identities\n Build the recidivism measurement framework: how often banned actors return, how fast we catch them, and which controls reduce return rates\n Author playbooks for contractor-supported evasion review with QA against your own gold standard\n Keep up to date with emerging AI policy enforcement best practices, and use these to inform our decision-making and workflows\n \n Minimum qualifications\n \n Experience investigating ban evasion, multi-accounting, or repeat fraud actors at a platform with adversarial users\n Fluency in SQL and comfort building your own analyses across large account and event datasets\n Experience working with fraud or identity-linking signals and a working understanding of their precision/recall tradeoffs\n Rigor about evidence standards — comfort with the asymmetric cost of false positives in severe-harm enforcement\n A track record of turning one-off investigations into repeatable detection logic and policy\n Strong written communication skills, with experience producing clear briefs and recommendations for technical and non-technical stakeholders\n Excellent judgment and the ability to collaborate with team members while navigating rapidly evolving priorities and workstreams\n \n Preferred qualifications\n \n Experience using payment or network risk signals in an enforcement context\n Experience with child-safety or other high-severity integrity enforcement\n Experience collaborating directly with detection engineering or data science teams on rule deployment\n A deep interest in AI safety and responsible technology development\n Experience writing effective prompts for generative AI systems in a content review or enforcement context\n \n  \n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $245,000 — $285,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous","salary_min":245000,"salary_max":285000,"location":"New York, NY","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["alignment","generative-ai","payments","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5319592008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-14T03:07:48Z","expires_at":"2026-08-14T14:00:31.34117Z","created_at":"2026-07-15T14:00:31.46483Z","updated_at":"2026-07-15T14:00:31.46483Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6fc9c11a-5817-4f35-acb7-d96f007c4325"},{"id":"7befba03-6985-475e-9441-9bd1ccb173d8","company_id":"a0000000-0000-0000-0000-000000000001","title":"Research Engineer, Chip Design RL (Reinforcement Learning)","slug":"research-engineer-chip-design-rl-reinforcement-learning-39e9d4d0","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the RL teams \n Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Fable 5 and Opus 4.8. Our work spans several key areas:\n \n Developing systems that enable models to use computers effectively\n Advancing code generation through reinforcement learning\n Pioneering fundamental RL research for large language models\n Building scalable RL infrastructure and training methodologies\n Enhancing model reasoning capabilities\n \n We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish.\n About the role \n We're hiring for the Code RL team within the RL organization. As a Research Engineer, you'll advance our models' ability to design silicon. Hardware design is difficult and unforgiving – exactly the sort of domain we want Claude to excel at.\n You'll leverage your chip design expertise and turn it into tasks and signals for models to learn from. Specifically, you will: \n \n Invent, design, and implement RL environments and evaluations for agentic RTL generation, design (including formal) verification, physical design optimization.\n Work on cross-cutting RL considerations such as EDA-tool latency optimization and proxy rewards.\n Conduct experiments and shape our roadmap.\n Deliver your work into research and production training runs.\n Collaborate with other researchers and engineers across and outside Anthropic.\n \n You may be a good fit if you: \n \n Have expertise in ASIC or FPGA design: RTL, design verification (UVM, formal methods, coverage-driven), physical design (synthesis, place-and-route, timing closure), PPA optimization, DFT, ECOs.\n Are fluent with industry EDA tools and processes.\n Have taped out chips and have experience going from spec to silicon.\n Know how to balance research exploration with engineering implementation.\n Are passionate about AI's potential and committed to developing safe and beneficial systems.\n \n Strong candidates may also have: \n \n Experience with reinforcement learning, evaluations or environments.\n Built tooling or automation around chip design flows.\n Worked on ML accelerators or high-performance compute hardware.\n Familiarity with high-level synthesis or architecture simulators.\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $500,000 — $850,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To","salary_min":500000,"salary_max":850000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["code-generation","reinforcement-learning","fine-tuning","search","llm","alignment","agents","research"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5231612008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-13T22:19:12Z","expires_at":"2026-08-14T14:00:27.276583Z","created_at":"2026-07-15T14:00:27.407964Z","updated_at":"2026-07-15T14:00:27.407964Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/7befba03-6985-475e-9441-9bd1ccb173d8"},{"id":"c7233a70-8734-418e-977e-e64fadd481c4","company_id":"a0000000-0000-0000-0000-000000000001","title":"Safeguards Enforcement Analyst, Cyber Harm ","slug":"safeguards-enforcement-analyst-cyber-harm-3292bc78","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role\n As an Enforcement Analyst, you will be responsible for reviewing content and executing enforcement actions across our products and services, with a focus on detecting and mitigating attempts to misuse Anthropic's AI systems for malicious cyber operations. Your initial focus will center on reviewing flagged activity related to cyberattacks, malware development, and offensive exploitation; however, this position may later expand to include broader areas of enforcement.\n Safety is core to our mission, and you'll help uphold policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way.\n Important context for this role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a violent, technical, or psychologically disturbing nature. This role may require responding to escalations during weekends and holidays.\n Key responsibilities\n \n Review flagged content and accounts to make accurate, well-documented enforcement decisions in line with our usage policies\n Detect and mitigate potential misuse of AI systems to facilitate cyberattacks, malware creation, exploitation tooling, and related harmful cyber operations\n Triage and escalate novel, ambiguous, or high-severity cases to appropriate stakeholders\n Provide detailed feedback to the Safeguards policy design team on policy gaps surfaced through real enforcement scenarios\n Partner with Engineering and Data Science teams by surfacing detection model errors and quality signals from review to improve precision and recall\n Maintain high accuracy and consistency standards across review queues\n Keep up to date with emerging AI policy enforcement best practices, threat actor tactics, and the evolving cyber threat landscape, using these to inform enforcement decisions\n \n Minimum Qualifications\n \n Experience in cybersecurity, including knowledge of offensive techniques, exploit development, malware analysis, or vulnerability research\n Experience performing content review, abuse investigations, or policy enforcement at volume\n Proficiency in SQL and/or Python for data analysis and threat detection\n Experience identifying emerging risks and communicating findings to a diverse set of stakeholders, such as Product, Policy, Engineering, and Legal teams\n Experience working with generative AI products, including writing effective prompts for content review and enforcement\n \n Preferred qualifications\n \n Experience in trust \u0026 safety, abuse investigations, cybersecurity investigations, or threat intelligence in a technology or AI company\n Experience with large language models and an understanding of how AI technology could be misused for cyber operations\n Experience operating within abuse monitoring programs or enforcement review systems\n Understanding of the challenges involved in implementing product policies at scale, including in the content moderation space\n Experience working with government agencies, regulated environments, or information sharing communities\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $285,000 — $330,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application ","salary_min":285000,"salary_max":330000,"location":"New York, NY","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["security","llm","alignment","generative-ai","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5311159008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-10T23:43:23Z","expires_at":"2026-08-14T14:00:31.672652Z","created_at":"2026-07-12T14:00:28.485977Z","updated_at":"2026-07-15T14:00:31.83111Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/c7233a70-8734-418e-977e-e64fadd481c4"},{"id":"cd912b35-ee12-4a3e-90a8-0abe74a80b0d","company_id":"a0000000-0000-0000-0000-000000000001","title":"Safeguards Enforcement Analyst, Integrity \u0026 Authenticity ","slug":"safeguards-enforcement-analyst-integrity-authenticity-941cc4f1","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role\n As a Safeguards Analyst focusing on Integrity \u0026 Authenticity, you will be responsible for building and executing enforcement workflows for our products and services, with a focus on detecting and mitigating attempts to misuse Anthropic's AI systems for coordinated inauthentic behavior, election manipulation, and targeting, tracking, and surveillance of individuals.\n Your work will span a broad and interconnected set of harm areas: AI-enabled influence operations and disinformation campaigns, the abuse of AI to interfere with electoral processes, and the use of AI systems to facilitate stalking, surveillance, profiling, and the targeting of individuals or groups. Safety is core to our mission, and you'll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way.\n Important context for this role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a political, violent, or psychologically disturbing nature. This role may require responding to escalations during weekends and holidays, particularly around major electoral events. \n Key responsibilities\n \n Design and architect automated enforcement systems and review workflows that scale effectively while maintaining high accuracy\n Partner with Engineering and Data Science teams to optimize detection models for policy violations and automated enforcement systems\n Review flagged content to drive enforcement and policy improvements\n Enforce usage policies with a focus on detecting and mitigating AI-enabled influence operations, coordinated inauthentic behavior, election interference, and targeting, tracking, or surveillance of individuals and groups\n Support the Safeguards policy design team by providing detailed feedback on policy gaps based on real enforcement scenarios\n Keep up to date with emerging AI policy enforcement best practices, evolving threat actor tactics, and the regulatory landscape around elections, privacy, and surveillance, using these to inform our decision-making and workflows\n \n Minimum qualifications\n \n Experience in trust \u0026 safety, policy enforcement, threat intelligence, or a closely related field with a focus on one or more of: influence operations, disinformation, coordinated inauthentic behavior, election integrity, or privacy and surveillance harms\n Experience standing up and scaling policy enforcement or content review workflows\n Proficiency in SQL and/or other data analysis tools to draw insights from large datasets\n Experience identifying emerging risks and threat actors, and communicating findings to a diverse set of stakeholders, such as Product, Policy, Engineering, and Legal teams\n Experience working with generative AI products, including writing effective prompts for content review and enforcement\n Understanding of the challenges involved in implementing product policies at scale, including in the content moderation space\n \n Preferred qualifications\n \n Experience conducting cross-platform investigations into influence operations, coordinated inauthentic behavior, or disinformation campaigns\n Familiarity with open-source intelligence (OSINT) techniques and tools used for threat actor tracking and network analysis\n Working knowledge of privacy law, surveillance technology, or data broker ecosystems as they relate to targeting and tracking harms\n Experience with large language models and an understanding of how AI technology could be misused to generate synthetic personas, fabricate quotes, or automate persuasion at scale\n Familiarity with election security frameworks, campaign finance law, or electoral integrity standards in one or more jurisdictions\n Experience navigating evolving regulatory landscapes relevant to this space (e.g., DSA, EU AI Act, FEC regulations, GDPR)\n Experience working with election bodies, civil society organizations, or government agencies on integrity or disinformation-related issues\n Proficiency in Python for data analysis and automation\n Experience with dark web monitoring or tracking threat actors across surface, deep, and dark web environments\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $285,000 — $330,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A ","salary_min":285000,"salary_max":330000,"location":"New York, NY","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","alignment","generative-ai","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5311149008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-10T23:40:28Z","expires_at":"2026-08-14T14:00:31.940387Z","created_at":"2026-07-12T14:00:28.575559Z","updated_at":"2026-07-15T14:00:32.073371Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/cd912b35-ee12-4a3e-90a8-0abe74a80b0d"},{"id":"624a206a-77bf-4580-8cdd-be32f7688f73","company_id":"a0000000-0000-0000-0000-000000000001","title":"Red Team Engineer, Safeguards","slug":"red-team-engineer-safeguards-ce8b1599","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role \n Anthropic's Safeguards team is seeking a Red Team Engineer to help ensure the safety of our deployed AI systems and products. In this role, you'll take an adversarial approach to uncover vulnerabilities across our product ecosystem before they can be exploited by malicious actors. Your work will span from technical infrastructure vulnerabilities on our products to emergent risks from advanced AI capabilities.\n While you'll bring best practices from traditional security approaches, the focus is on broader safety implications and novel abuse unique to advanced AI systems and associated products. You'll investigate the full spectrum of potential abuse — from coordinated account manipulation and payment fraud to novel exploitation of product features — and simulate sophisticated threat actors who chain multiple attack vectors to achieve their objectives.\n Key responsibilities \n \n Conduct comprehensive adversarial testing across Anthropic's product surfaces, developing creative attack scenarios that combine multiple exploitation techniques\n Research and implement novel testing approaches for emerging capabilities, including agent systems, tool use, and new interaction paradigms\n Design and execute \"full kill chain\" attacks that emulate real-world threat actors attempting to achieve specific malicious objectives\n Build and maintain systematic testing methodologies that evaluate every aspect of our systems\n Develop automated testing frameworks to enable continuous assessment at scale\n Collaborate with Product, Engineering, and Policy teams to translate findings into concrete improvements\n Help establish metrics for measuring detection effectiveness of novel abuse\n \n Minimum qualifications \n \n Experience in penetration testing, red teaming, or application security\n Experience in model jailbreaking and testing large-scale agentic workflows for non-obvious prompt injection vectors\n Strong technical skills in web application security, including hands-on expertise with security testing tools (e.g., Burp Suite, Metasploit, custom scripting frameworks)\n Experience building custom automation, including LLM-specific testing frameworks\n A track record of discovering novel attack vectors and chaining vulnerabilities in creative ways\n A public body of work such as CVEs, blog posts, or disclosed bug bounty reports\n Strong written and verbal communication skills, with the ability to explain technical concepts to varied audiences\n \n Preferred qualifications \n \n Experience with AI/ML security or adversarial machine learning\n Understanding of AI safety considerations beyond traditional security, including modern guardrails against jailbreaks\n Experience testing API security and rate-limiting systems\n Background in testing business logic vulnerabilities and authorization bypass techniques\n Background in anti-fraud, trust \u0026 safety, or abuse prevention systems\n Familiarity with distributed systems and infrastructure security\n Familiarity with abuse detection mechanisms and the ability to engineer novel bypasses\n Adaptability to understand and build engagements around emerging threats outside your direct area of expertise\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $320,000 — $405,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, s","salary_min":320000,"salary_max":405000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["distributed-systems","security","agents","llm","payments","alignment","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5320469008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-10T22:50:56Z","expires_at":"2026-08-14T14:00:26.778559Z","created_at":"2026-07-12T14:00:24.449098Z","updated_at":"2026-07-15T14:00:26.90493Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/624a206a-77bf-4580-8cdd-be32f7688f73"},{"id":"27e47bb2-457a-411c-94da-c13b0a26bbe4","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Software Engineer, Financial Fraud","slug":"staff-software-engineer-financial-fraud-e46a39b4","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role \n The Fraud Prevention team protects Anthropic's payment and monetization surfaces from financial abuse — keeping fraud losses, dispute rates, and network monitoring exposure in check while preserving a smooth experience for legitimate customers. As a software engineer on this team, you will build the systems that make risk decisions in real time, manage the dispute and chargeback lifecycle, and detect monetization abuse across subscriptions, in-app purchases, and promotions. The ideal candidate can see things from attackers' perspectives, anticipate their responses to countermeasures, and never loses sight of the fact that a false positive here is a paying customer.\n Payments fraud is more externally coupled than most trust and safety work — you'll collaborate closely with finance, support, and legal teams internally, and with payment processors and platform partners externally.\n Responsibilities: \n \n Design and build real-time risk decisioning that scores transactions at authorization time, balancing fraud loss, approval rates, and latency constraints\n Build tooling and automation for the dispute and chargeback lifecycle, from review queues to evidence collection and loss reporting\n Engineer fraud signals at scale — device fingerprinting, BIN and issuer signals, velocity features, and cross-account linkage — and detect monetization abuse across subscriptions, trials, promotions, and in-app purchases\n Own a portfolio of metrics — loss rate, dispute rate, authorization approval impact, and false-positive rate — rather than optimizing any single number\n Lead investigations into emerging fraud patterns, building multi-layered defenses designed for attacker adaptation rather than point-in-time rules\n Work cross-functionally with finance, support, legal, and data science, and with external payment processors and platform partners\n \n Minimum Qualifications:  \n \n Proficiency in Python, SQL, and data analysis tools\n Experience building or operating fraud, risk, or abuse detection systems in production\n Strong communication skills and ability to explain complex technical tradeoffs to non-technical stakeholders\n \n Preferred Qualifications:  \n \n 8+ years of industry software engineering experience, with a focus on payments fraud or risk\n Fluency with payments rails: card networks, payment service providers (e.g., Stripe, Adyen), in-app purchase platforms (Apple, Google), refund flows, and the chargeback and dispute lifecycle\n Direct experience combating fraud typologies such as card testing, stolen-card monetization, refund and chargeback abuse, subscription and trial abuse, promotional abuse, and friendly fraud\n Understanding of fraud loss accounting — fraud loss vs. dispute fees vs. card network monitoring programs (e.g., VDMP, i VFMP, Mastercard ECP) — and why chargeback rate thresholds carry existential stakes\n Experience building hybrid rules-and-ML risk systems: real-time scoring at authorization plus post-authorization review workflows\n Experience at a marketplace or subscription business, or on a processor-side or issuer-side risk team\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $320,000 — $485,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely ","salary_min":320000,"salary_max":485000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["alignment","payments","fintech","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5325909008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-10T20:42:40Z","expires_at":"2026-08-14T14:00:37.455206Z","created_at":"2026-07-12T14:00:33.033504Z","updated_at":"2026-07-15T14:00:37.614587Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/27e47bb2-457a-411c-94da-c13b0a26bbe4"},{"id":"0350a954-0064-4e8b-8175-872842961d14","company_id":"a0000000-0000-0000-0000-000000000001","title":"Platform Security Engineering, Auditor","slug":"platform-security-engineering-auditor-3b75119c","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role \n We're seeking a vulnerability assessment candidate for platform security. You'll work cross functionally with teams across Anthropic and our partners to assess security features in hardware, firmware, bootloaders, operating systems, and attestation systems to identify and remove vulnerabilities from the ground up.\n This role requires expertise in low-level systems security and the ability to audit the most security-critical platform elements. This is not a role where you can simply file a ticket and hope that the fixes get into production and stay in production. The role requires taking ownership that everything you find is eliminated fully and correctly in production, including ensuring known vulnerabilities are never reintroduced.\n Key responsibilities \n \n Audit secure boot chains from firmware through OS initialization for diverse hardware platforms (CPUs, BMCs, switches, peripherals, and embedded microcontrollers)\n Audit attestation systems that provide cryptographic proof of system state from hardware root of trust through application layer\n Audit measured boot implementations and runtime integrity monitoring\n Integrate security controls with infrastructure teams without impacting training performance\n Validate security mechanisms before production deployment\n Conduct firmware vulnerability assessments and penetration testing\n Build firmware vulnerability assessment pipelines for continuous security monitoring\n Document security architectures and maintain threat models\n Collaborate with software and hardware vendors to ensure security capabilities meet our requirements for exploit mitigation\n \n Minimum qualifications  \n \n Proven track record of conducting hands-on vulnerability auditing on complex, security-critical systems\n Hands-on experience with secure boot, measured boot, and attestation technologies (TPM, Intel TXT, AMD SEV, ARM TrustZone)\n Strong understanding of cryptographic protocols and hardware security modules\n Experience with UEFI/BIOS or embedded firmware security, bootloader hardening, and chain of trust implementation\n Proficiency in low-level programming languages (C, Assembly) and systems programming\n Knowledge of firmware vulnerability assessment and threat modeling\n Ability to work effectively across hardware and software boundaries\n Strong communication and cross functional collaboration skills\n Track record of assessing security architectures for complex, distributed systems\n \n Preferred qualifications \n \n 8+ years of experience in systems security, with at least 5 years focused on low-level security (firmware, bootloaders, and OS kernel-level security)\n Capacity to audit for logic bugs in code written in Rust or Go\n Ability to find vulnerabilities via reverse engineering in software that is provided only in binary form\n Experience performing fault injection \u0026 side-channel analysis attacks on hardware\n Experience auditing silicon root of trust implementations\n Experience auditing confidential computing technologies and hardware-based TEEs\n Background in formal verification or security proof techniques\n 5 or more talks at top-tier security conferences with candidate listed as first author\n Experience using LLMs to automate security assessment (including tooling creation)\n Experience securing large-scale HPC or cloud infrastructure\n Previous work with AI/ML infrastructure security\n \n  \n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $320,000 — $405,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will ","salary_min":320000,"salary_max":405000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["cloud","distributed-systems","security","llm","alignment"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5316565008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-10T20:04:07Z","expires_at":"2026-08-14T14:00:24.876792Z","created_at":"2026-07-12T14:00:22.963819Z","updated_at":"2026-07-15T14:00:25.186516Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0350a954-0064-4e8b-8175-872842961d14"},{"id":"df926b58-0b03-4baf-bf2e-041b21f1c314","company_id":"12105b3e-eb1d-4a92-95b6-855042facaf1","title":"Principal Product Manager, Core AI Platform","slug":"principal-product-manager-core-ai-platform-a86ff672","description":"At Qualtrics, we create software the world’s best brands use to deliver exceptional frontline experiences, build high-performing teams, and design products people love. But we are more than a platform—we are the creators and stewards of the Experience Management category serving over 18K clients globally. Building a category takes grit, determination, and a disdain for convention—but most of all it requires close-knit, high-functioning teams with an unwavering dedication to serving our customers.\n When you join one of our teams, you’ll be part of a nimble group that’s empowered to set aggressive goals and move fast to achieve them. Strategic risks are encouraged and complex problems are solved together, by passing the mic and iterating until the best solution comes to light. You won’t have to look to find growth opportunities—ready or not, they’ll find you. From retail to government to healthcare, we’re on a mission to bring humanity, connection, and empathy back to business. Join over 5,000 people across the globe who think that’s work worth doing.\n Principal Product Manager, Core AI Platform \n Why We Have This Role \n \n Define the future of the core AI infrastructure that powers intelligent experiences across Qualtrics.\n Build the platform capabilities that enable product teams to create trusted, scalable, and differentiated AI experiences using structured and unstructured experience data.\n Own the product strategy for foundational AI capabilities such as ontologies and semantic systems, agent infrastructure, context and memory, tools and orchestration, agent evaluation, observability, and AI safety.\n Manage the entire lifecycle for multiple functional areas of the Core AI Platform, from framing the problem, to aligning on architecture and product direction, to forming the plan, delivering implementation, and iterating until the capabilities are world-class.\n \n How You’ll Find Success \n \n Partner with product, engineering, data science, research, and design teams across Qualtrics to understand the infrastructure and platform capabilities required to build exceptional AI products.\n Develop a deep understanding of the needs of both enterprise customers and internal AI product builders, and translate those needs into platform strategy, requirements, and roadmaps.\n Define product strategy for foundational AI capabilities, including areas such as ontologies and semantic layers, agent runtimes and orchestration, tool use, context engineering, memory, model access, agent evaluation, observability, and guardrails.\n Prioritize platform investments based on customer value, developer productivity, technical leverage, reuse across Qualtrics products, and opportunities for competitive differentiation.\n Collaborate deeply with engineering, AI research, and data science teams to make thoughtful product and architectural tradeoffs in a rapidly evolving technical landscape.\n Develop clear frameworks for evaluating the quality, reliability, safety, and business impact of agentic AI systems.\n Create shared platform capabilities that accelerate AI development across Qualtrics while providing the reliability, governance, security, and observability required by enterprise customers.\n Develop and communicate a compelling vision and roadmap for the Core AI Platform to senior leaders, product teams, technical stakeholders, and customers.\n Define and monitor meaningful KPIs for platform adoption, AI quality, evaluation performance, developer velocity, reliability, and customer impact.\n Stay at the forefront of developments in agents, foundation models, evaluation methods, context engineering, semantic systems, and enterprise AI infrastructure—and translate those developments into concrete product opportunities for Qualtrics.\n \n How You’ll Grow \n \n By shaping the technical and product foundations for the next generation of AI experiences across Qualtrics.\n Through developing deep expertise in emerging areas such as agent architecture, ontologies, semantic systems, evaluation, and AI infrastructure.\n By making high-leverage product decisions that influence multiple product lines and teams.\n Through leading complex, ambiguous initiatives that require alignment across product, engineering, research, data science, security, and go-to-market organizations.\n By developing your ability to connect rapidly evolving AI technologies to durable customer value and differentiated product strategy.\n \n Things You’ll Do \n \n Develop and execute the product strategy for Qualtrics’ Core AI Platform.\n Define the foundational architecture and capabilities required for teams across Qualtrics to build reliable, differentiated AI experiences.\n Lead product strategy for areas including:\n \n Ontologies, semantic layers, and grounding AI systems in the meaning and relationships within enterprise experience data.\n Agent infrastructure, including orchestration, planning, tool use, delegation, and multi-agent patterns.\n Agent evaluati","salary_min":199500,"salary_max":262000,"location":"Seattle, WA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["agents","healthcare","alignment","generative-ai","llm"],"apply_url":"https://www.qualtrics.com/careers/us/en/job/8055389?gh_jid=8055389","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-10T19:52:16Z","expires_at":"2026-08-14T14:21:25.801786Z","created_at":"2026-07-12T14:17:18.150005Z","updated_at":"2026-07-15T14:21:25.899556Z","company_name":"Qualtrics","company_slug":"qualtrics","company_logo_url":"https://www.google.com/s2/favicons?domain=qualtrics.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/df926b58-0b03-4baf-bf2e-041b21f1c314"},{"id":"cf91d42b-0197-48eb-98e4-035f8da8d708","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Application Security Engineer  - M\u0026A  ","slug":"staff-application-security-engineer-ma-94810600","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role\n Anthropic's Application Security team secures the systems that build, serve, and increasingly are Claude — and as Anthropic's footprint grows, that mandate now extends to companies and codebases we bring in from outside. This role establishes that function.\n You'll own security due diligence and secure integration for Anthropic's acquisitions — assessing a target's security posture pre-close, writing the security risk readout for leadership, and after close, bringing acquired systems up to Anthropic's bar. Security has been part of every deal to date, but this is the first dedicated role for it: you'll formalize the playbook, the risk model, and the tooling, and make them repeatable.\n This is an AppSec role first. You'll be an active member of the Application Security team — same rituals, same on-run rotation, same tooling, working alongside engineers securing Anthropic's own agentic product surfaces. The expectation is the same too: we use Claude as our primary tool, and you're expected to automate the repeatable parts of diligence and integration as you go, so each acquisition is easier than the last. When deal flow is quiet, you'll pick up core AppSec project work; when it's active, M\u0026A is your priority.\n We're upfront that the center of gravity here is M\u0026A rather than core product security. It's burstier, more assessment-heavy, and operates on confidential, time-sensitive work. If you like parachuting into an unfamiliar codebase under time pressure and turning it into a clear risk picture for leadership, this is that job.\n Key responsibilities\n \n Lead pre-close security due diligence on prospective acquisitions — coordinate external penetration testing, threat-model the target's architecture, assess security controls, and deliver the security risk readout for leadership ahead of close and integration planning\n Drive post-close security integration — stand up static and dynamic analysis coverage on acquired codebases, track high- and critical-severity remediation to closure, fold acquired assets into bug bounty scope, and onboard repositories to Anthropic's automated vulnerability remediation and reporting systems\n Coordinate adjacent security engineering teams (supply chain, cloud, corporate security, detection \u0026 response) on their portions of each integration\n Work across a wide set of stakeholders on every deal — corporate development, legal, security leadership, and the engineering teams inheriting acquired systems internally; engineering and security counterparts at the target company externally — translating between them and keeping the security workstream legible to all of them\n Formalize and scale Anthropic's M\u0026A security playbook — risk-scoring model, diligence runbook, integration checklist — and turn as much of it as possible into Claude-powered tooling rather than manual process\n Share the team's operational on-run rotation (bug bounty escalations, launch consults, incident response), swapping out during periods of active deal work\n Contribute to core AppSec projects between deals — secure design reviews, threat modeling for agentic systems, and the team's security automation roadmap\n \n Minimum qualifications\n \n Hands-on application and infrastructure security experience, including cloud and containerized environments\n Demonstrated ability to rapidly assess an unfamiliar codebase or architecture and produce a clear, prioritized risk assessment for a non-security audience\n Production-quality coding ability in at least one of Python, Go, Rust, or TypeScript\n Practical threat-modeling and vulnerability-identification skills — you've found and reasoned about real bugs in real systems\n Comfort operating with high autonomy, ambiguity, and tightly-held confidential context\n Clear written and verbal communication across varied audiences — executives, legal and corporate development partners, and engineering counterparts at an acquired company\n \n Preferred qualifications\n \n 7+ years in application security, security consulting, or security architecture\n Prior M\u0026A security due diligence, third-party security assessment, or technical due diligence experience\n Experience standing up or scaling SAST/DAST, bug bounty, or vulnerability management coverage across multiple codebases\n Track record of building security automation or tooling rather than relying solely on manual review\n Familiarity with using LLMs as a core part of your security workflow\n Experience securing agentic, code-execution, or LLM-integrated systems\n \n Representative projects\n \n Point Anthropic's internal LLM-driven code analysis and AI-assisted scanning at an a","salary_min":320000,"salary_max":485000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["agents","llm","alignment","security"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5311463008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-10T19:05:32Z","expires_at":"2026-08-14T14:00:34.868848Z","created_at":"2026-07-12T14:00:31.037737Z","updated_at":"2026-07-15T14:00:34.995365Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/cf91d42b-0197-48eb-98e4-035f8da8d708"},{"id":"5e84a3b7-6396-4e2c-a48f-c1dae6573539","company_id":"a0000000-0000-0000-0000-000000000001","title":"Finance Systems Integration Engineer","slug":"finance-systems-integration-engineer-c4f39bc4","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role \n We are seeking an experienced Finance Systems Integration Engineer to support our finance systems transformation at one of the fastest-growing AI companies. You'll design and build integrations connecting our ERP platform with critical financial applications and support our ERP implementation initiatives. As you master our integration landscape, you'll have opportunities to expand into Claude-powered AI automation and data pipeline development.\n You'll build the integration backbone for one of the fastest-growing AI companies, with a front-row seat to how Claude transforms financial operations. This is a foundational role where you'll shape our integration architecture from the ground up, then expand into cutting-edge AI automation as our needs evolve. You'll work alongside teams building frontier AI systems while directly applying that technology to solve real financial operations challenges.\n In this role you will: \n Core Focus: Integration Development \u0026 ERP Support \n \n Design, build, and maintain integrations connecting ERP systems with downstream applications including ZipHQ, Brex, Navan, Clearwater, Payroll systems, Salesforce, and other critical financial platforms using Workato, MuleSoft, or similar iPaaS solutions\n Support integration development and testing during the ERP implementation projects \n Develop and maintain REST APIs, webhooks, and OAuth 2.0 authentication flows for secure system-to-system communication\n Implement real-time and batch integration patterns supporting high-volume financial transactions\n Establish monitoring, alerting, and error-handling frameworks to ensure integration reliability and data integrity\n Document integration architectures, data flows, API specifications, and troubleshooting procedures\n Collaborate with implementation consulting partners and vendors on technical integration requirements\n \n Additional Scope:  AI Automation \u0026 Data Infrastructure \n As you master our integration landscape, you'll have opportunities to expand into:\n AI Agent Development \n \n Build and deploy Claude-powered AI agents that automate financial operations including intelligent document processing, workflow automation, financial audit and reconciliations, and self-service reporting\n Design agentic workflows that leverage Claude API capabilities integrated with ERP platform data and processes\n Create automated validation and quality assurance processes for AI-generated outputs\n Partner with Finance teams to identify automation opportunities and translate requirements into AI agent solutions\n \n Data Pipeline Support \n \n Support data pipeline development using Airflow for workflow orchestration and dbt for data transformation\n Build and maintain data flows from ERP and other financial systems into BigQuery for analytics and reporting\n Implement data quality checks and testing frameworks for financial data pipelines\n Collaborate with Data Infrastructure team on pipeline architecture, performance optimization, and security monitoring\n Support executive dashboards and financial analytics by ensuring timely, accurate data delivery\n \n Governance \u0026 Collaboration \n \n Maintain comprehensive documentation for integrations, AI agents, and data pipelines\n Support internal and external audits with technical evidence and system access reviews\n Collaborate with Finance Systems Engineers on operational support, troubleshooting, and enhancement requests\n Partner with Finance Operations, Accounting, FP\u0026A, Engineering, and Data Infrastructure teams to deliver holistic solutions\n \n You may be a good fit if you: \n \n Have 8+ years of experience in integration development, data engineering, or systems engineering roles\n Possess hands-on experience with iPaaS platforms such as Workato, MuleSoft, Dell Boomi, or similar integration tools\n Have strong programming skills in Python and/or JavaScript/TypeScript for building custom integrations, APIs, and automation scripts\n Demonstrate experience with data pipeline tools including Airflow for orchestration and dbt for transformation\n Have working knowledge of cloud data platforms such as BigQuery, Snowflake, or Databricks\n Understand REST API design patterns, webhooks, OAuth 2.0, and modern integration architectures\n Have familiarity with ERP systems (Oracle Fusion, Workday Financials, or similar) and financial business processes\n Possess strong problem-solving skills with ability to debug complex integration issues across multiple systems\n Thrive in a fast-paced, high-growth environment balancing innovation with operational stability\n Have excellent communication skills to collaborate with technical and business sta","salary_min":205000,"salary_max":270000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","agents","payments","alignment","api-design","data-pipeline"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5315789008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-09T14:27:46Z","expires_at":"2026-08-14T14:00:21.627236Z","created_at":"2026-07-10T14:00:23.500172Z","updated_at":"2026-07-15T14:00:21.788573Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/5e84a3b7-6396-4e2c-a48f-c1dae6573539"},{"id":"eeeae1ee-77ec-47e2-8f3a-01c65044747d","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff Software Engineer, Labs: Applied AI","slug":"staff-software-engineer-labs-applied-ai-8a0854db","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role\n At Anthropic, we're building AI systems that are safe, beneficial, and transformative. Our mission is to develop AI that benefits humanity, and we believe the most powerful capabilities emerge when we thoughtfully bridge the gap between research breakthroughs and real-world applications.\n  \n Applied AI is one of the newest explorations within Anthropic Labs, the internal accelerator behind Claude Code, MCP, and Claude Design. Most of the world's work happens far from a code editor, and the people doing it have barely begun to feel what frontier AI can do. We believe Claude has a transformative role to play here — and we're at the earliest stage of exploring what that could look like. The engineers who join now will define where it goes.\n  \n We're looking for versatile, entrepreneurial engineers who are energized by building for users unlike themselves. In this role, you'll take frontier AI capabilities and turn them into applications that professionals in less software-native roles can pick up and trust — rapidly building and testing new experiences, partnering directly with researchers, domain experts, and users, and generating the insights that shape where this exploration goes next. You'll need to be comfortable with ambiguity, willing to kill your own projects when the data says to, and energized by the pace of building in uncharted territory.\n Responsibilities\n \n \n Rapidly prototype full-stack applications that bring frontier AI into workflows that have never been software-first, shipping early and often to maximize learning\n \n Immerse yourself in unfamiliar domains: sit with users, learn how their work actually gets done, and encode that understanding into products, evaluations, and workflows\n \n Collaborate closely with research teams to understand new model capabilities and translate them into tools that non-technical professionals reach for first\n \n Work directly with internal teams and external partners across industries to gather feedback, iterate quickly, and validate (or invalidate) product concepts\n \n Design and run structured experiments to test hypotheses, balancing creative exploration with rigorous evaluation\n \n Generate documentation and insights to guide successful prototypes toward full product teams\n \n Provide feedback to research teams about model effectiveness in real-world, domain-heavy settings and where capabilities can improve\n \n Flexibly contribute across Labs initiatives based on organizational priorities and emerging opportunities — context from one project should inform the next\n \n You may be a good fit if you\n \n \n Have 8+ years of experience building full-stack applications, with a track record of zero-to-one work in startup or startup-like environments\n \n Are deeply curious about how other industries work, and enjoy translating messy, real-world workflows into simple software\n \n Thrive in ambiguity and are energized (not anxious) by uncertainty — you're comfortable working on projects that might not exist in three months\n \n Have a hacker mentality: high agency, bias toward shipping, comfort with technical debt when it's the right tradeoff\n \n Are deeply user-centric — you validate ideas with actual users before over-investing and talk about problems before solutions\n \n Can articulate learnings from failed or killed projects without defensiveness; you treat your work as experiments\n \n Hold strong opinions loosely — you advocate forcefully for ideas but change your mind based on evidence\n \n Are a generalist who can transition between different problem spaces as priorities shift\n \n Work independently with good judgment about what matters, without needing constant direction\n \n Communicate effectively and can make complex AI capabilities feel intuitive to people who don't think in software\n \n Care about the societal impacts and ethics of your work\n \n Strong candidates may also have\n \n \n Experience building products for industries outside of tech — e.g., healthcare, manufacturing, logistics, construction, energy, agriculture, financial services, education, or the public sector\n \n A previous career, or deep hands-on exposure, in a field outside of software — you've been the user these products serve\n \n Background conducting embedded or field-based discovery: user research, interviews, ride-alongs, and usability testing with frontline professionals\n \n Experience integrating with the systems these industries actually run on (ERPs, EHRs, CRMs, dispatch, scheduling, or point-of-sale systems)\n \n Experience shipping software or AI applications to non-technical or frontline users — you know how to design for people wh","salary_min":320000,"salary_max":405000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","healthcare","fine-tuning","alignment"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5304425008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T19:55:29Z","expires_at":"2026-08-14T14:00:38.266563Z","created_at":"2026-07-09T14:00:41.408804Z","updated_at":"2026-07-15T14:00:38.403947Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/eeeae1ee-77ec-47e2-8f3a-01c65044747d"},{"id":"8962baa3-07f0-4de5-bdc8-24e9482b4c58","company_id":"a0000000-0000-0000-0000-000000000001","title":"Threat Intel Manager, Model Exploitation \u0026 Fraud","slug":"threat-intel-manager-model-exploitation-fraud-a7445668","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role \n We are looking for a threat intel manager to build and run our Model Exploitation \u0026 Fraud team within Threat Intelligence. This team detects, investigates, and disrupts the large-scale exploitation of Anthropic's AI systems. Model distillation,  unauthorized access, account farming and reseller abuse, and fraud and scam operations.\n You will set the strategy for the mission area, hire and lead a small team of technical investigators, and build the systems, processes, and partnerships that let the team scale. The team includes established senior investigators who own our deepest technical casework,  tracing distillation networks, reseller and proxy ecosystems, and financially motivated actors across first-party surfaces and third-party platforms; your job is to direct, resource, and amplify that work, not duplicate it. This area carries regular U.S. government engagement and requires deeply understanding external black market ecosystems and how they interact with our systems.\n Important context: In this position you may be exposed to explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature. This role may require responding to escalations during weekends and holidays. \n Key responsibilities \n \n Own strategy, priorities, and outcomes for the Model Exploitation \u0026 Fraud mission area; define what we detect, investigate, action, and share\n Hire, manage, and develop a team of technical threat investigators; set the quality bar for casework and intelligence reporting\n Design clear lanes between this role and the team's senior individual contributors: strategy, people leadership, and program ownership sit with you, while ownership of the deepest technical investigations and tradecraft stays with the senior experts closest to the work\n Capable of independently leading complex investigations. \n Direct, prioritize, and resource complex investigations into model distillation, unauthorized AI R\u0026D usage, unauthorized access, coordinated account abuse, and fraud/scam networks, partnering with the senior investigators who lead the deepest technical casework and clearing blockers from their path\n Drive the redesign of triage for a very high-volume detection pipeline: partner with investigators and engineering to build abuse signals, clustering, and agentic investigation workflows that separate sophisticated actors from noise\n Expand the team's coverage into fraud and scams, building the detection and investigation playbooks from the ground up\n Own the external engagement program for the area, including regular intelligence sharing with U.S. government partners and industry peers, ensuring the investigators driving the work are visible in those channels\n Anticipate how resellers, proxies, and third-party platforms change the abuse surface, and shape coverage accordingly\n Work with policy, enforcement, and engineering to convert findings into bans, product mitigations, and safety-by-design improvements\n Define and report the team's metrics; brief Safeguards and company leadership on the threat landscape\n \n Minimum qualifications \n \n Have led and managed investigative, fraud, platform integrity, or threat intelligence teams, ideally ones built around senior, deeply specialized individual contributors\n Have strong domain fluency in scaled abuse — fraud patterns, account abuse, unauthorized access, or platform exploitation economics — sufficient to set priorities, pressure-test findings, and earn the confidence of expert investigators\n Are proficient enough in SQL and Python to review data-heavy casework, pressure-test conclusions, and provide surge capacity when the team needs it\n Have experience overseeing investigations that track threat actors across surface, deep, and dark web environments, including reseller and access-broker communities\n Have working familiarity with large language models and a strong grasp of how models can be distilled, extracted, or exploited at scale\n Have built processes, detection systems, or programs from scratch and can show what changed because of them\n Communicate crisply with executives, engineers, and external partners alike\n \n Preferred qualifications \n \n Experience at a major technology platform on trust and safety, fraud, or abuse investigations at scale\n Background in financial crime investigation or fraud analytics\n Experience working directly with U.S. government stakeholders on threat reporting\n A track record of partnering with, growing, and retaining senior technical specialists, including defining clear scope between management and senior IC tracks\n Fluency in Man","salary_min":375000,"salary_max":455000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["llm","agents","alignment","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5305476008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T19:02:57Z","expires_at":"2026-08-14T14:00:41.172292Z","created_at":"2026-07-09T14:00:43.257037Z","updated_at":"2026-07-15T14:00:41.304633Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8962baa3-07f0-4de5-bdc8-24e9482b4c58"},{"id":"50df2b7e-cf30-4c96-ac78-97a1fe5311c1","company_id":"a0000000-0000-0000-0000-000000000001","title":"Threat Intel Manager, Influence Operations \u0026 Surveillance","slug":"threat-intel-manager-influence-operations-surveillance-38cdcd24","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role \n We are looking for a threat intel manager to build and run our Influence Operations \u0026 Surveillance team within Threat Intelligence. This team detects, investigates, and disrupts the misuse of Anthropic's AI systems for influence operations, coordinated inauthentic behavior, and surveillance operations by authoritarian states and the commercial spyware ecosystem. \n This is a ground-floor leadership role. The mission area today produces some of our most consequential casework and external reporting almost entirely through manual investigation; you will stand up its purpose-built detection capabilities, set the strategy for how a frontier AI company finds and counters state-linked information manipulation and surveillance misuse, and you'll personally be involved with the most complex investigations.\n Important context: In this position you may be exposed to explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature. This role may require responding to escalations during weekends and holidays. \n Key responsibilities \n \n Own strategy, priorities, and outcomes for the Influence Operations \u0026 Surveillance threat intel mission area\n Hire, manage, and develop a small team of technical threat investigators with IO and surveillance expertise\n Personally lead investigations into state-linked surveillance misuse  including commercial spyware vendors and surveillance products whose end customers are authoritarian governments and AI-enabled influence campaigns\n Stand up the mission area's first automated detection: abuse signals, behavioral clustering, and coordinated-network detection tailored to information manipulation and surveillance tooling\n Conduct cross-platform analysis linking on-platform activity to broader campaigns across social media, messaging platforms, and the spyware supply chain\n Attribute campaigns to specific actors, with particular focus on state-sponsored operations from geopolitically significant regions\n Own external engagement: government partners, platform integrity teams, academic and civil-society researchers, and threat intelligence sharing communities\n Drive public and partner-facing reporting on AI-enabled IO and surveillance, and inform safety-by-design strategies as multimodal and agentic capabilities reshape the landscape\n \n Minimum qualifications \n \n Have deep subject matter expertise in influence operations, coordinated inauthentic behavior, or state surveillance / commercial spyware ecosystems\n Have led investigative teams or threat intel teams. \n Have demonstrated proficiency in SQL and Python for data analysis and threat detection\n Have experience attributing campaigns to specific threat actors, including state-sponsored operations\n Have strong OSINT tradecraft for investigating online information ecosystems\n Have hands-on experience with large language models and how they can be weaponized for IO and surveillance\n Can present analytical work to technical and non-technical audiences, including government stakeholders and senior leadership\n \n Preferred qualifications \n \n Experience at a major technology platform on influence operations, platform integrity, or content authenticity\n Background in intelligence analysis, information operations, or counter-disinformation in government or military contexts\n Experience investigating commercial spyware or surveillance-as-a-service vendors (e.g., civil-society or vendor-research backgrounds)\n Experience investigating operations linked to Chinese, Russian, Iranian, or other state-sponsored campaigns\n Fluency in Mandarin Chinese, Russian, Farsi, and/or Arabic with nuanced regional and geopolitical context\n Familiarity with social network analysis for mapping coordinated behavior\n Active Top Secret security clearance\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $375,000 — $455,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some r","salary_min":375000,"salary_max":455000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["agents","alignment","llm","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5302779008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T03:22:40Z","expires_at":"2026-08-14T14:00:41.07544Z","created_at":"2026-07-09T14:00:43.170356Z","updated_at":"2026-07-15T14:00:41.206124Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/50df2b7e-cf30-4c96-ac78-97a1fe5311c1"},{"id":"5ae0b189-6a5f-411a-892b-43657c20a151","company_id":"a0000000-0000-0000-0000-000000000001","title":"Applied AI Architect, Partnerships ","slug":"applied-ai-architect-partnerships-1c077648","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role: \n As a Partners Solutions Architect on the Applied AI team at Anthropic, you will be a Pre-Sales architect focused on cultivating technical relationships with our Global and Regional System Integrators (GSIs/RSIs), and our cloud partners (AWS and GCP). You will strengthen our relationships with key partners to accelerate indirect revenue, enable their AI practices, and execute on long-term GTM strategy.\n Responsibilities: \n \n \n Strategic Technical Partnership : Be a technical thought partner to the Anthropic GTM partnerships team, providing technical expertise to better understand the partner landscape, driving key strategic programs, and identifying opportunities to deepen partner technical capabilities. Embed with GSI and cloud partner technical teams to enable their AI practices, support troubleshooting, evangelize Anthropic in their developer communities, and serve as an escalation point for complex technical issues.\n \n Joint Solution Development: Collaborate with partners to identify high value industry-specific GenAI applications, develop joint solutions and codify reference architectures / best practices to accelerate time to deployment\n \n Customer Deal Support:  Intervene directly to unblock strategic customer deals where partners are the primary delivery vehicle, providing deep technical expertise and solution architecture guidance.\n \n Partner Ecosystem \u0026 Events: Represent Anthropic at partner events such as GSI customer workshops, AWS summits, and industry conferences. Lead or support partner-specific developer events, hackathons, and technical enablement sessions, especially for technically native communities.Product Feedback: Validate and gather feedback on Anthropic's products and offerings, especially as they relate to partner use cases and deployment patterns, and deliver this feedback to relevant Anthropic teams to inform product roadmap and partner strategy.\n \n You may be a good fit if you have: \n \n \n 5+ years of experience in technical customer-facing/partner-facing roles such as Solutions Architect, Sales Engineer, Partner Sales Engineer, Technical Account Manager\n \n Track record of successfully partnering with GSIs and/or cloud providers to solve complex technical challenges, from initial solution design through customer delivery\n \n Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering \u0026 IT teams, and more\n \n Strong presentation \u0026 technical communication skills with the ability to translate requirements between technical and business stakeholders\n \n Experience designing scalable cloud architectures and integrating with enterprise systems\n \n Familiarity with common LLM frameworks and tools or a background in machine learning or data science\n \n Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities\n \n A love of teaching, mentoring, and helping others succeed\n \n Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $275,000 — $380,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, ","salary_min":275000,"salary_max":380000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","alignment","generative-ai","cloud"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5300430008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-07T16:38:52Z","expires_at":"2026-08-14T14:00:16.868026Z","created_at":"2026-07-09T14:00:22.938408Z","updated_at":"2026-07-15T14:00:17.010159Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/5ae0b189-6a5f-411a-892b-43657c20a151"},{"id":"5d222f90-90c4-4238-b68f-02a7bee00eaf","company_id":"a0000000-0000-0000-0000-000000000001","title":"Engineering Manager, Research Data Platform","slug":"engineering-manager-research-data-platform-40a3e0af","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role\n Anthropic's researchers generate and depend on enormous amounts of data — training runs, evaluations, RL transcripts, annotations etc... The Research Data Platform team builds the systems that make that data easy to produce, find, query, and trust. We work in two modes: we build  platform components that other systems plug into (for example, a metrics library that training frameworks integrate to record and retrieve run data), and we own core datasets end to end (for example, the data pipeline behind RL transcripts).\n As the team's tech lead, your job starts with our users. You'll work directly with researchers — and with the engineers who support them — to understand how they actually work, where managing data slows them down, and where a well-built platform component or a well-curated dataset would change what's possible. You'll turn what you learn into technical direction for the team, in partnership with the team's manager, who owns priorities and people. A central ambition you'll drive: a small set of canonical, well-documented datasets — starting with the core data model for RL — that researchers trust and standardize on, rather than every team managing its own copies.\n You'll spend your first few months close to the code and close to users: shipping improvements in our core systems, embedding with research teams, and building your own map of their workflows. As the team grows, this role has a natural path into formal people leadership for someone who wants it.\n Responsibilities\n \n Work directly with researchers and the engineers supporting them to understand their workflows, identify the highest-leverage opportunities, and shape what the team builds next\n Set the technical direction for the team across our platform and our datasets\n Design and build platform components that other teams plug into — libraries, services, and interfaces such as the metrics library used by training frameworks\n Own core datasets end to end: the pipelines that produce them, the schemas that define them, and the documentation and guarantees that make researchers trust them\n Drive convergence toward canonical datasets — including the core data model for RL transcripts — that research teams standardize on\n Lead complex, multi-quarter projects that span several systems and teams, staying hands-on in the code\n Raise the team's technical bar through design reviews, mentorship, and the quality of your own work\n \n You may be a good fit if you:\n \n Have built and operated data-intensive systems at scale — pipelines, storage layers, query systems — with strong instincts for data modeling and schema design that hold up as usage grows\n Have set technical direction for a team, or owned the architecture of a data platform that other teams build on\n Treat internal users as customers: you do the discovery work, iterate with users, and measure success by adoption rather than by shipping\n Understand that researchers aren’t typical internal customers — the work is exploratory by nature, workflows differ from team to team, and requirements are discovered through experiments rather than specified up front\n Can build for that motion — keeping interfaces stable and data trustworthy while use cases change underneath you, and judging when a quick, disposable solution serves research better than a durable one\n Lead through influence — aligning engineers and stakeholders without relying on formal authority\n Are results-oriented and pragmatic, willing to do unglamorous work when it's the highest-leverage thing\n Are excited about learning the fundamentals of machine learning research (deep ML expertise is not required)\n Care about the societal impacts of your work\n \n Strong candidates may also have\n \n Experience with large-scale ETL and columnar or analytical storage (e.g., Spark, BigQuery, ClickHouse, DuckDB, Parquet)\n Experience with metrics or experiment-tracking systems, or high-volume time-series data\n Experience with dataset management, cataloging, or lineage tooling\n Built developer tooling or internal data platforms for demanding technical users — including in domains like quantitative trading, where fast-moving, exploratory data work looks a lot like research\n A working knowledge of machine learning\n Worked in, or closely with, an ML research lab\n Interest in — or experience with — people management and growing engineers\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual","salary_min":405000,"salary_max":850000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["fine-tuning","alignment","data-pipeline","research"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5297059008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-07T02:44:47Z","expires_at":"2026-08-14T14:00:20.895077Z","created_at":"2026-07-07T14:00:21.432276Z","updated_at":"2026-07-15T14:00:21.024892Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/5d222f90-90c4-4238-b68f-02a7bee00eaf"},{"id":"e4e8f26d-a735-40ce-846f-4cc7f9bf655b","company_id":"01048ffd-9864-41e0-a719-14b849fbcbcd","title":"Principal AI Engineer, Special Programs","slug":"principal-ai-engineer-special-programs-6c6075fc","description":"SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today SpaceX is actively developing the technologies to make this possible, with the ultimate goal of enabling human life on Mars.\n PRINCIPAL AI ENGINEER, SPECIAL PROGRAMS \n This team focuses on engineering and deploying AI capabilities (models, APIs, tools, and integrations) for U.S. federal agencies. You'll work closely with product, research, infrastructure, and legal/governance teams to make  AI and future models maximally useful for missions while upholding safety, transparency, and ethical standards.\n RESPONSIBILITIES: \n \n Design, build, and optimize integrations between AI frontier models (e.g., Grok family) and government systems, platforms, and data environments\n Collaborate on custom SDKs, APIs, developer tools, and documentation tailored for government and enterprise developers\n Partner with agency stakeholders to understand requirements, prototype solutions, and iterate rapidly based on real-world feedback\n Ship production-grade code and features with a bias toward speed, simplicity, and measurable impact\n \n BASIC QUALIFICATIONS: \n \n Bachelor's degree in computer science or another STEM discipline; OR 2+ years of professional experience in software development in lieu of a degree\n 6+ years of hands-on software engineering experience building scalable systems, APIs, or AI/ML applications (strong Python proficiency, other languages a plus)\n \n PREFERRED SKILLS AND EXPERIENCE: \n \n Experience working with large language models, generative AI, or agentic systems—either in research, production, or applied engineering\n Familiarity with government or public sector technology environments (federal civilian agencies, state/local gov, or regulated industries like healthcare, finance, or infrastructure)\n Strong product sensibility: ability to translate ambiguous stakeholder needs into concrete technical solutions\n Demonstrated ability to write clean, maintainable, high-performance code under tight timelines\n Exceptional problem-solving skills and intellectual curiosity—you thrive on hard, ambiguous challenges\n Excellent communication skills; you can explain complex technical concepts to non-technical partners clearly and concisely\n Prior work on AI safety, governance, red-teaming, or responsible AI deployment\n Experience with cloud platforms (AWS, GCP, Azure), containerization (Docker/Kubernetes), or API orchestration\n Background in policy-adjacent technical roles, civic tech, or public-interest technology\n Contributions to open-source AI projects or developer tools\n \n ADDITIONAL REQUIREMENTS: \n \n Must be willing to work extended hours and weekends as needed\n 20% travel may be required to government sites\n This position requires successfully obtaining and maintaining a Top Secret Security Clearance as a condition of employment. While the clearance may not be immediately necessary upon hire, we encourage you to initiate the application process promptly upon accepting this offer. Your ability to secure the necessary clearance is essential for fulfilling key responsibilities of the role. Should you be unable to obtain it, SpaceX reserves the right to modify or terminate your employment to align with operational needs.\n \n COMPENSATION AND BENEFITS: \n Pay range:     Principal AI Engineer: $220,000.00 - $350,000.00/per year    \n Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, and experience.\n Base salary is just one part of your total rewards package at SpaceX. You may also be eligible for long-term incentives, in the form of company stock, stock options, or long-term cash awards, as well as potential discretionary bonuses and the ability to purchase additional stock at a discount through an Employee Stock Purchase Plan. You will also receive access to comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short and long-term disability insurance, life insurance, paid parental leave, and various other discounts and perks. You may also accrue 3 weeks of paid vacation and will be eligible for 10 or more paid holidays per year. Employees accrue paid sick leave pursuant to Company policy which satisfies or exceeds the accrual, carryover, and use requirements of the law.\n ITAR REQUIREMENTS: \n \n To conform to U.S. Government export regulations, applicant must be a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (aka green card holder), (iii) Refugee under 8 U.S.C. § 1157, or (iv) Asylee under 8 U.S.C. § 1158, or be eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here .  \n \n SpaceX is an Equal Opportunity Employer; employment with SpaceX is governed on the basis of merit, competence and qualifications and will not be influenced","salary_min":220000,"salary_max":350000,"location":"Washington, DC","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["alignment","healthcare","agents","llm","generative-ai"],"apply_url":"https://boards.greenhouse.io/spacex/jobs/8572114002?gh_jid=8572114002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-06T18:38:41Z","expires_at":"2026-08-14T14:19:55.728364Z","created_at":"2026-07-07T14:26:20.977051Z","updated_at":"2026-07-15T14:19:55.918752Z","company_name":"SpaceX","company_slug":"spacex","company_logo_url":"https://www.google.com/s2/favicons?domain=spacex.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e4e8f26d-a735-40ce-846f-4cc7f9bf655b"}],"market_demand_pack":{"amount_cents":2900,"api_checkout_url":"https://aidevboard.com/api/v1/checkout?product_id=aidevboard_ai_skills_demand_pack","checkout_url":"https://aidevboard.com/market-demand-pack?qc=api-jobs-market-demand-pack\u0026utm_campaign=skills_demand_pack\u0026utm_medium=jobs_api\u0026utm_source=api","currency":"USD","description":"Full ranked public AI/ML demand CSV, source job URLs, and decision brief with market and offer angles.","fulfillment":"automatic_email_after_paid_checkout","human_checkout_url":"https://aidevboard.com/market-demand-pack?qc=api-jobs-market-demand-pack\u0026utm_campaign=skills_demand_pack\u0026utm_medium=jobs_api\u0026utm_source=api","name":"AI Market Demand Pack","next_step":"Open checkout_url for Stripe Checkout, or call api_checkout_url to get the non-charging checkout handoff payload.","price_usd":29,"product_id":"aidevboard_ai_skills_demand_pack","quote_url":"https://aidevboard.com/api/v1/quote?product_id=aidevboard_ai_skills_demand_pack"},"page":1,"per_page":20,"total":396,"total_pages":20}