{"access":{"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","employer_pilot_url":"https://aidevboard.com/verified-interview-pilot","mode":"open","register_url":"https://aidevboard.com/api/v1/register"},"candidate_resume_action":{"application_authorized":false,"candidate_charge":0,"endpoint":"https://aidevboard.com/api/v1/candidate/resume-preview","job_id_json_path":"jobs[].id","method":"POST","preview_requires_identity":false,"required_body_fields":["job_id","evidence_bullets"],"requires_explicit_human_review":true,"saved_artifact_protocol":"mcp","saved_artifact_requires_verified_human":true,"saved_artifact_tool":"compile_job_specific_resume","search_requires_identity":false,"status":"available_after_candidate_selects_job","submission_performed":false,"uses_candidate_verified_evidence":true},"degraded":false,"estimated":false,"has_next":true,"jobs":[{"id":"6146aded-8614-4fdf-a457-cef73b78ddbe","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Fullstack Software Engineer, Safeguards Engineering","slug":"staff-fullstack-software-engineer-safeguards-engineering-c0ee19d3","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 Note: this job post is for Fullstack Software Engineers only. If you are a Backend Engineer, please see our Backend Software Engineer post  here .  \n About the role \n We are looking for fullstack software engineers to help build safety and oversight mechanisms for our AI systems. As a software engineer on the Safeguards team, you will work to monitor models, prevent misuse, and ensure user well-being. This role will focus on building systems to detect unwanted model behaviors and prevent disallowed use of models. You will apply your technical skills to uphold our principles of safety, transparency, and oversight while enforcing our terms of service and acceptable use policies.\n We have multiple teams that are currently hiring within Safeguards. Team placement occurs after the interview process, taking into account your interests and experience alongside organizational needs. This flexible approach allows us to match talented engineers where they'll have the greatest impact and growth potential.  \n Responsibilities: \n \n Design and build the internal review tools analysts use to investigate abuse — dashboards, case queues, and evidence viewers that make high-volume, high-stakes decisions fast and accurate.\n Build the interfaces where humans supervise agents: streaming output, interruption and approval flows, and clear provenance for every action an agent takes.\n Surface abuse patterns to our research teams through the visualizations and exploration tools that make emerging patterns legible.\n Own the frontend architecture for tools handling sensitive data at scale — performance under large datasets, correctness under real-time updates, and access controls enforced end to end.\n \n You may be a good fit if you have: \n \n A Bachelor’s degree in Computer Science, Software Engineering or comparable experience\n Proficiency in TypeScript and modern React; comfortable in Python for backend work\n The ability to work across the stack\n Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders\n \n Strong candidates may also: \n \n 8+ years of experience in a software engineering position, not including internships or co-ops\n Have experience building data-dense internal tools or operator interfaces, not just marketing or consumer surfaces\n Have experience with integrity, spam, fraud, or abuse detection and mitigation\n Have experience building trust and safety detection mechanisms and intervention for AI/ML systems\n Have experience with prompt engineering, jailbreak attacks, and other adversarial inputs\n Have worked closely with operational teams to build custom internal tooling\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 $405,000 — $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 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,","salary_min":405000,"salary_max":485000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["alignment","fine-tuning","rust","fullstack"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5369710008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-09T14:55:52Z","expires_at":"2026-11-13T16:54:56.598201Z","created_at":"2026-10-14T15:17:23.066476Z","updated_at":"2026-10-14T16:54:56.601343Z","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/6146aded-8614-4fdf-a457-cef73b78ddbe"},{"id":"e93a2a59-96bf-439e-aeab-74ec34d72a67","company_id":"a0000000-0000-0000-0000-000000000018","title":"Machine Learning Engineer, Trust \u0026 Safety","slug":"machine-learning-engineer-trust-safety-fc325068","description":"About Vercel:\n Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. \n Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. \n About the Role:\n We are looking for a Machine Learning Engineer on our Trust \u0026 Safety Engineering team, to build and operate the production systems that detect and stop abuse on the platform at internet scale. This is an engineering-first role, roughly 80% writing and shipping production code (services, pipelines, and infrastructure) and 20% modeling, taking detection and classification approaches from prototype to hardened systems. This is a hybrid role based in San Francisco or New York City, with three days a week in the office.\n What you’ll do: \n \n Design, build, and operate production systems that detect and disrupt abusive behavior across the platform, with an emphasis on reliability, scalability, and observability\n Build and maintain machine learning (ML) infrastructure, including training pipelines, feature pipelines, serving infrastructure, and evaluation frameworks\n Ship large language model (LLM) and classical ML approaches for abuse detection and classification, turning prototypes into maintainable code\n Own systems end to end, from integrating a model into the platform through deployment, monitoring, and iteration\n Work with security, product, and infrastructure teams to turn abuse patterns and detection logic into production systems\n \n What you need: \n \n 5+ years of software engineering experience building and operating production systems at scale\n Wrote production code in Python, plus JavaScript/TypeScript or Go\n Built and maintained ML infrastructure, such as training and serving pipelines, feature stores, or evaluation tooling\n Integrated LLMs into production systems, including prompt engineering and evaluation\n \n Bonus if you: \n \n Built an open source ML tool\n Worked in the trust and safety, fraud, or abuse prevention domain\n \n Compensation \u0026 Benefits:\n \n Competitive compensation package, including equity.\n Inclusive Healthcare Package.\n Learn and Grow - we provide mentorship and send you to events that help you build your network and skills.\n Flexible Time Off.\n We will provide you the gear you need to do your role, and a WFH budget for you to outfit your space as needed.\n \n The San Francisco, CA base pay range for this role is $208,000.00 - $312,000.00. Actual salary will be based on job-related skills, experience, and location. Compensation outside of San Francisco may be adjusted based on employee location. The total compensation package may include benefits, equity-based compensation, and eligibility for a company bonus or variable pay program depending on the role. Your recruiter can share more details during the hiring process. \n \n Disclosures: \n \n Privacy: Please review our Job Applicant Privacy Policy for more information on how we handle your data.\n Equal Opportunity:  Vercel is committed to fostering and empowering an inclusive community within our organization. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law. Vercel encourages everyone to apply for our available positions, even if they don't necessarily check every box on the job description.","salary_min":208000,"salary_max":312000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","healthcare","agents","machine-learning","rust"],"apply_url":"https://job-boards.greenhouse.io/vercel/jobs/6208037004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-09T04:59:47Z","expires_at":"2026-11-13T16:55:41.948472Z","created_at":"2026-10-14T15:19:47.726056Z","updated_at":"2026-10-14T16:55:41.951722Z","company_name":"Vercel","company_slug":"vercel","company_logo_url":"https://www.google.com/s2/favicons?domain=vercel.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e93a2a59-96bf-439e-aeab-74ec34d72a67"},{"id":"355cddc4-1109-480c-9753-ab804302195a","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Software Engineer, Account Abuse (Machine Learning)","slug":"staff-software-engineer-account-abuse-machine-learning-ae303349","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 Account Abuse team is tasked with ensuring Anthropic's computing capacity is allocated fairly, minimizing resources available to bad actors and preventing them from coming back. As a software engineer on this team, you will build the machine learning systems that help us detect and stop abuse at scale. The ideal candidate can see things from opponents' perspectives, understand their means and motives, and anticipate their responses to countermeasures.\n We're looking for full stack machine learning engineers with experience across model training, productionization, and evaluation. You'll also look for ways to use Claude to speed up how these models get built and maintained.\n This is classical ML on structured and behavioral data. You do not need a deep learning background or knowledge of LLM internals. What matters is that you have trained and shipped models where the stakes are real, and that you care about building robust production systems as much as the model itself. A false positive here is a legitimate customer locked out, so measurement, precision, and safe rollout are part of the job.\n Key responsibilities \n \n Build and operate a feature computation platform that serves both model training and real-time scoring, with point-in-time correct training data and low-latency online retrieval\n Train, evaluate, and deploy models that detect account-level abuse and fraud, running them both offline and online\n Build tooling that automates more of the model development lifecycle, including using Claude to speed up feature development, training, and evaluation\n Make backtesting, shadow deployment, and staged rollout the default path to production, with monitoring for training / serving skew, drift, and adversarial adaptation\n Work with our data scientists and our Policy \u0026 Enforcement team to improve label coverage and quality\n Partner with product and platform teams to gather signals and integrate model decisions with minimal impact on their systems' latency, stability, or overall architecture\n \n Minimum qualifications \n \n Proficiency in Python and SQL\n Experience training machine learning models and deploying them to production\n Experience building data pipelines with a batch processing engine (e.g., Spark, Beam) and a workflow scheduler (e.g., Airflow)\n Working understanding of point-in-time correctness and training / serving skew, and how to prevent both\n Strong communication skills and ability to explain technical tradeoffs to non-technical stakeholders\n \n Preferred qualifications \n \n Experience building or operating a feature platform such as Chronon, Feast, or Tecton\n Experience with stream processing engines such as Flink, Beam / Dataflow, or Kafka Streams\n Experience training ML models in a production setting with demanding serving requirements, such as fraud, risk, or ranking\n Experience with tree-based models on tabular data\n Experience building unsupervised, clustering-based or graph-based detection systems to surface coordinated account abuse\n Experience in integrity, spam, fraud, or abuse detection\n Experience working with scarce, delayed, or noisy labels\n Experience with AutoML or other approaches to automating the ML workflow\n Care about the societal impacts of AI and want your work to make powerful systems safer\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 b","salary_min":320000,"salary_max":485000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","alignment","data-pipeline","deep-learning","machine-learning","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5436293008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-28T20:31:13Z","expires_at":"2026-11-13T16:54:56.684975Z","created_at":"2026-10-14T15:17:23.151497Z","updated_at":"2026-10-14T16:54:56.687848Z","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/355cddc4-1109-480c-9753-ab804302195a"},{"id":"50eb2e11-551c-4b8e-93fc-a4f106c28663","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Software Engineer, Distributed Systems ","slug":"staff-software-engineer-distributed-systems-6695bd5f","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 software engineers to help build safety and oversight mechanisms for our AI systems. As a software engineer on the Safeguards team, you will work to monitor models, prevent misuse, and ensure user well-being. This role will focus on building distributed and scalable systems to detect unwanted model behaviors and prevent disallowed use of models. You will apply your technical skills to uphold our principles of safety, transparency, and oversight while enforcing our terms of service and acceptable use policies.\n Responsibilities: \n \n Independently scope and lead complex, multi-month infrastructure projects, from an ambiguous starting point through to a production system\n Develop monitoring systems to detect unwanted behaviors from our API partners and potentially take automated enforcement actions; surface these in internal dashboards to analysts for manual review\n Stand up and run deployments of those monitoring systems across multiple clouds, including inside cloud-provider partner environments where data residency laws apply. Keep the deployments consistent through shared deployment pipelines, smoke tests, observability, and alerting\n Design and harden the sandboxed runtime that AI agents execute in: isolation, network egress controls, least-privilege data access, audit logging, and insider-risk controls\n Manage cost and capacity for large volumes of long-running agent work, and set and meet service-level objectives for the platform\n Partner with the engineers and researchers who write and evaluate the monitoring agents, and with security, privacy, and legal teams, so new detection work can ship quickly on a platform everyone trusts\n \n You may be a good fit if you: \n \n Bachelor’s degree in Computer Science, Software Engineering or comparable experience\n Proficiency in Python, Distributed Systems, and Infrastructure as Code\n Have worked across multiple cloud providers, or built infrastructure designed to be provider-agnostic\n Have built and operated large-scale, distributed infrastructure, such as data platforms, control planes, or job schedulers\n Have experience with sandboxing and isolation technologies (containers, microVMs, network policy) or with a systems language such as Rust\n Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders\n \n Strong candidates may also: \n \n 8+ years of experience in a software engineering position, not including internships\n Have built systems that handle sensitive or regulated data, with requirements around access control, auditability, retention, and data residency\n Have experience running LLM-based agents in production\n Have experience with integrity, spam, fraud, or abuse detection and mitigation\n \n Deadline to apply: None. Applications will be reviewed on a rolling basis.\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 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 o","salary_min":320000,"salary_max":485000,"location":"New York, NY","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["distributed-systems","agents","cloud","llm","alignment","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5424404008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-15T13:43:35Z","expires_at":"2026-11-13T16:54:56.798784Z","created_at":"2026-10-14T15:17:23.272927Z","updated_at":"2026-10-14T16:54:56.802216Z","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/50eb2e11-551c-4b8e-93fc-a4f106c28663"},{"id":"2d764a21-548d-4995-b28e-a419ab251185","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Software Engineer, ML Inference Path","slug":"staff-software-engineer-ml-inference-path-b64fb22d","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 Safeguards ML Inference Path team designs, builds, and operates the production infrastructure that powers Claude's ML based safety systems. We collaborate closely with safety researchers and inference engineers to bring new classifiers and novel classes of ML defenses to production. We own the research → production transfer of new safety technologies that is on the critical path for every Claude model launch. And we build for scale: serving thousands of ML classifiers, for all requests on the token generation path, and for every platform Claude runs on -- 1P, Bedrock, Vertex, and beyond.\n We’re growing the team and looking for engineers who have deep expertise in productionizing ML systems. You'll work at the intersection of machine learning, large-scale distributed systems, and AI safety, developing the platforms and tools that enable our safeguards to operate reliably at scale. And your tooling and infrastructure will be used for every model launch, which are becoming more complex, and more frequent.\n Responsibilities: \n \n Design and build scalable ML infrastructure to support real-time safety deployments across our classifier and model ecosystem\n Build monitoring and observability tools to track classifier performance, data quality, and system health for safety-critical applications\n Collaborate with research teams to productionize safety research, translating experimental safety techniques into robust, scalable systems\n Optimize inference latency and throughput for real-time safety evaluations while maintaining high reliability standards\n Implement automated testing, deployment, and rollback systems for ML models in production safety applications\n Partner with Safeguards, Security, and Alignment teams to understand requirements and deliver infrastructure that meets safety and production needs\n Contribute to the development of internal tools and frameworks that accelerate safety research and deployment\n \n You may be a good fit if you: \n \n Are proficient in Python and have experience with ML frameworks like PyTorch, TensorFlow, or JAX\n Understand distributed systems principles and have built systems that handle high-throughput, low-latency workloads\n Have built automated or self-service deployment pipelines and eval infrastructure allowing researchers to roll out classifiers and models independently\n Have implemented A/B testing frameworks and experimentation infrastructure for ML systems\n Are results-oriented, with a bias towards reliability and impact in safety-critical systems\n Enjoy collaborating with researchers and translating cutting-edge research into production systems\n Care deeply about AI safety and the societal impacts of your work\n \n Strong candidates may also have experience with: \n \n Have 5+ years of experience building production ML infrastructure, ideally in safety-critical domains like fraud detection, content moderation, or risk assessment\n Working with large language models and modern transformer architectures\n Developing monitoring and alerting systems for ML model performance and data drift\n Experience in trust \u0026 safety, fraud prevention, or content moderation domains\n Knowledge of privacy-preserving ML techniques and compliance requirements\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 e","salary_min":320000,"salary_max":485000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["tensorflow","distributed-systems","llm","alignment","pytorch","inference","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5419869008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-09T19:19:17Z","expires_at":"2026-11-13T16:54:56.888395Z","created_at":"2026-09-10T13:30:51.32706Z","updated_at":"2026-10-14T16:54:56.891101Z","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/2d764a21-548d-4995-b28e-a419ab251185"},{"id":"8b77ea04-5765-490a-966c-cfd6746b16dd","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Software Engineer, ML Sampling Path","slug":"staff-software-engineer-ml-sampling-path-4534cff4","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 Safeguards ML Sampling Path team builds and operates the production services that power Claude's safety systems. These services sit on the token generation path across every platform Claude runs on: every request must pass through them, and each millisecond of added latency is wait time for our users. You’ll keep p99 latency flat as traffic grows, build for robustness as dependencies time out or partially fail, and ship changes safely to a system that cannot go down.\n What you'll do: \n \n Design, build, and operate the backend systems that process every token on the generation path for Claude requests, including the streaming contract with the API and inference engines.\n Own latency and reliability end to end: define and maintain SLOs and error budgets for added latency, time-to-first-token, and availability, and lead incident response and postmortem follow-through.\n Ship changes to the hot path rapidly but safely — canaried and gradual rollouts, error budget and latency gating, fast rollbacks — and drive per-token performance: chase tail latency and keep cost flat as traffic, models, and checks per request grow.\n Set technical direction for the sampling path: lead design reviews, make latency, reliability, and cost trade-off calls with the inference and research teams, mentor engineers, and raise the operational bar for the wider Safeguards organization.\n \n You may be a good fit if you: \n \n Have designed, built, and operated high QPS systems at global scale, and were accountable for them in production: incident response, outages, and postmortem-driven remediation.\n Have a strong foundation in distributed systems: replication, consistency tradeoffs, failure modes, and SLO management under load.\n Design systems for graceful degradation: you plan for a slow dependency, a dropped stream, or a half-rolled-out deploy before it happens, and build so the system degrades predictably instead of failing.\n Have successfully shipped broad or all-encompassing changes to mission critical systems (e.g., database migrations, interface changes, rewrites).\n \n Strong candidates may also have: \n \n 8+ years of industry software engineering experience.\n Familiarity with LLM inference systems and transformer-based models (not required, but a plus).\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 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 communication, don't click any links—visit  anthropic.com/careers  direc","salary_min":320000,"salary_max":485000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["distributed-systems","alignment","llm","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5419868008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-09T19:17:24Z","expires_at":"2026-11-13T16:54:56.893391Z","created_at":"2026-09-10T13:30:51.446194Z","updated_at":"2026-10-14T16:54:56.895979Z","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/8b77ea04-5765-490a-966c-cfd6746b16dd"},{"id":"48f5370e-0fca-4119-9914-073646b7089b","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Site Reliability Engineer, Safeguards ML Infra","slug":"staff-site-reliability-engineer-safeguards-ml-infra-14824a0d","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 Safeguards ML Infra team designs, builds, and operates the production infrastructure that powers Claude's safety systems. We own the critical backend services that ensure safety on the token generation path, and we own the operational work of getting those systems safely into production: standing up safeguards for every new model launch, and deploying new safety classifiers as they ship. Every frontier model release runs through this team – we configure, verify, and roll out safeguards across every platform Claude runs on (1P, AWS Bedrock, GCP Vertex, etc.), and we lead incident response when issues arise.\n This role sits at the center of that operational work. You'll ensure safeguards are properly configured and deployed for model launches and own the off-cycle deployment of new safety classifiers — canarying changes, verifying that the right safeguards are provably live on the right models, and holding rollback authority when something looks wrong. Every launch should also shrink the checklist, and the manual verifications should evolve into a system that runs itself. You'll turn launch runbooks into tooling, hand-built checks into continuous validation, and one-off deploys into a repeatable pipeline.\n We're looking for engineers with deep experience in production change management at scale — people who have owned deploy pipelines, config management systems, rollout safety, or launch readiness for systems under real production pressure. Familiarity with ML research or transformer architectures is not required — you will learn that on the job. What we prioritize is production judgment: a track record of shipping changes to critical systems safely, and of automating yourself out of the work you did last quarter.\n What you'll do: \n \n Launch captain model releases: stand up, configure, and verify safeguards for every new model, and serve as the safeguards point of contact in the launch room during release windows.\n Own the off-cycle deployment of new safety classifiers as they ship from research — canarying rollouts, running post-deploy validations, and investigating discrepancies when something looks wrong.\n Verify that the right safeguards are provably live on the right models across every deployment platform (1P, AWS Bedrock, GCP Vertex, etc.), and detect and eliminate configuration drift between them.\n Automate yourself out of last quarter's work: turn launch runbooks into tooling, hand-built checks into continuous validation, and one-off deploys into a repeatable pipeline.\n \n Plan to use Claude aggressively to do this! And be a trailblazer that paves the path for safe agentic operations of safety-critical systems.\n \n Build and maintain a safeguards registry with full provenance — what is running in production, on which model, on which platform, and when and by whom it was deployed.\n Participate in on-call and operational-duty rotations covering service incidents, model provisioning, and time-sensitive research and safety launches.\n \n You may be a good fit if you: \n \n Have owned production change management at scale — deploy pipelines, config management systems, canary analysis — and have strong opinions about what \"verified\" means.\n Have run high-stakes releases: served as a launch captain, incident commander, or release owner for systems where a bad deploy has real consequences, and are energized rather than drained by being in the critical path.\n Have meaningful on-call experience for production systems, including incident response and postmortem-driven improvements — and a track record of turning (and fixing!) postmortem action items into process and tooling changes.\n Have a desire to close the gap where nobody has yet raised their hand, even if it requires manually hand-holding processes until automation and tooling can be built.\n Have hands-on experience deploying and operating on cloud platforms (AWS, GCP) at scale.\n Are proficient in Python; experience with Rust is a plus but not required.\n \n Strong candidates may also have: \n \n 8+ years of industry software engineering or site reliability engineering experience.\n A demonstrated history of reducing operational toil through automation, including transitioning teams from manual deployment processes to self-serve pipelines.\n Experience running launch or production-readiness review processes across multiple teams.\n Familiarity with LLM inference systems and the operational characteristics of transformer-based models.\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 th","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","cloud","agents","llm","infrastructure","rust","devops"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5416709008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-04T17:02:37Z","expires_at":"2026-11-13T16:54:56.664214Z","created_at":"2026-09-05T13:30:36.213865Z","updated_at":"2026-10-14T16:54:56.667157Z","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/48f5370e-0fca-4119-9914-073646b7089b"},{"id":"1a84e14d-d7dc-4b61-9b07-5aceaf6b6ca3","company_id":"a0000000-0000-0000-0000-000000000001","title":"Research Manager, Biological Safety","slug":"research-manager-biological-safety-96a6f407","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 organization builds the policies, evaluations, and enforcement systems that keep our models from contributing to catastrophic harm. We are hiring a manager to lead the research engineering team responsible for biological safety: the evaluations, datasets, and classifiers that govern how our models handle biological knowledge.\n You will lead a team of research scientists and engineers who design and run capability evaluations against frontier models, curate training data for our safety classifiers, train and iterate on those classifiers alongside our ML engineers, and measure how they hold up against adversarial pressure in production traffic. You will set the technical direction for that work, decide where the team invests, and own the results.\n This is a hands-on management role. Most of your time goes to growing and directing the team, but you will keep enough technical depth to review an eval design, interrogate a classifier's failure modes, and represent the work credibly to Research, Product, and Policy partners.\n The core tension your team owns is precision: safeguards need to be robust against sophisticated actors while staying out of the way of the far larger population of legitimate researchers using Claude to accelerate life sciences work. Getting that tradeoff right is an empirical problem, and your team is the one measuring it.\n Key responsibilities \n \n \n Manage, coach, and grow a team of research scientists and engineers working on biological safety evaluations and classifiers, including hiring, onboarding, performance, and career development\n \n Set the technical direction and roadmap for the biological safety research agenda, and make the calls about what the team builds, what it deprioritizes, and when a safeguard is ready to ship\n \n Own the quality of capability evaluations that assess what new models can do in the biological domain, and turn results into deployment recommendations that leadership can act on\n \n Guide the development of training and evaluation datasets for our safety classifiers, working with internal and external threat modeling experts to ground them in realistic risk\n \n Oversee the training and iteration of safety classifiers alongside ML engineers, optimizing jointly for adversarial robustness and low false-positive rates\n \n Ensure the team invests in the tooling and pipelines that make evaluation and classifier development fast and repeatable\n \n Establish how the team measures classifier and eval performance against production traffic, identifies gaps, and prioritizes improvements\n \n Direct red-teaming and stress-testing of safeguards as threats, models, and product surfaces evolve\n \n Partner with Research, Product, Policy, and government affairs colleagues to embed biological safety throughout the model development lifecycle, and serve as an escalation point for biological content\n \n Represent the team's work in external communications including model cards, blog posts, and policy documents\n \n Track developments in biology, machine learning, and biosecurity for their potential to create new risks or enable new mitigations\n \n Minimum qualifications \n \n \n Experience managing a technical team, including hiring, coaching, and performance management\n \n A record of setting technical direction for a team and making prioritization calls under uncertainty\n \n Proficiency in Python, with a background in scientific programming and data analysis\n \n A solid grasp of ML fundamentals, sufficient to critically review evaluation design and classifier development\n \n Knowledge of modern biology across both measurement and engineering: high-throughput assays and functional characterization, as well as gene synthesis, genome editing, strain construction, and protein engineering\n \n Experience designing quantitative experiments or evaluations and drawing defensible conclusions from noisy results\n \n Clear analytical and writing skills, and the ability to explain technical concepts to non-technical stakeholders\n \n Familiarity with dual-use research concerns and biosecurity frameworks, such as select agent regulations, the Biological Weapons Convention, or Australia Group guidelines\n \n Comfort with ambiguity and with shifting priorities as AI capabilities change\n \n Motivation to prevent misuse without obstructing the beneficial work that makes up the vast majority of this field\n \n Preferred qualifications \n \n \n 3+ years of people management experience, ideally leading research scientists, research engineers, or ML engineers\n \n Experience building a team or function from a small headcount, including defining scope, hiring","salary_min":405000,"salary_max":485000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["fine-tuning","alignment","llm","search","research","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5412944008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-02T04:39:16Z","expires_at":"2026-11-13T16:54:56.239525Z","created_at":"2026-09-02T13:30:32.056604Z","updated_at":"2026-10-14T16:54:56.242302Z","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/1a84e14d-d7dc-4b61-9b07-5aceaf6b6ca3"},{"id":"51f12d71-50b2-4e11-96a7-cdac7d2c9ac2","company_id":"a0000000-0000-0000-0000-000000000001","title":"Safeguards Enforcement Analyst, Conventional Weapons","slug":"safeguards-enforcement-analyst-conventional-weapons-c5ef188a","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 Conventional Weapons, your work spans detecting and mitigating attempts to misuse Anthropic's AI systems to facilitate real-world harm, specifically utilizing conventional weapons and dangerous technology. 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. \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 \n Design and architect automated enforcement systems and review workflows that scale effectively while maintaining high accuracy\n \n Develop and maintain evals that measure model performance on these policy areas, surface regressions, and inform policy and model improvements\n \n Partner with Engineering and Data Science to optimize detection and automated enforcement systems for potential policy violations\n \n Review flagged content to drive enforcement decisions and surface policy gaps, with particular attention to novel or technically sophisticated misuse attempts + emerging tactics\n \n Support the Safeguards policy design team by providing structured feedback on policy gaps and enforcement ambiguities based on real enforcement scenarios\n \n Develop and maintain enforcement guidelines and reviewer documentation that enable accurate, consistent enforcement across a wide range of content\n \n Keep up to date with emerging weapons trends and applications, regulatory changes, and AI policy enforcement best practices, and apply these to inform our workflows and evals\n \n Identify and escalate emerging misuse patterns, novel attack vectors, and signs of coordinated violent activity\n \n Minimum qualifications \n \n \n Have deep, applied expertise in weapons systems and can translate complex technical evidence to make enforcement decisions\n \n Experience in policy enforcement, threat intelligence, counterterrorism, government, or a closely related field, with direct exposure to harmful content, dangerous technology, or physical harm facilitation\n \n Experience standing up and scaling policy enforcement or content review workflows\n \n Proficiency in SQL and/or other data analysis tools to draw insights from large datasets and monitor enforcement workflow health\n \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 \n Experience working with generative AI products, including writing effective prompts for content review and enforcement\n \n Understanding of the challenges involved in implementing product policies at scale, including in the content moderation space\n \n Preferred qualifications \n \n \n Subject matter expertise in conventional weapons and dangerous technology, autonomous systems, or critical infrastructure protection\n \n Familiarity with relevant legal and regulatory frameworks governing dangerous technology, conventional weapons, and critical infrastructure\n \n Experience developing evals or red-teaming AI systems, particularly for harmful content or policy enforcement use cases\n \n Experience with threat actor profiling and threat intelligence frameworks (e.g., MITRE ATT\u0026CK)\n \n Experience tracking threat actors, extremist networks, or misuse patterns across surface, deep, and dark web environments\n \n Experience with large language models and an understanding of how AI technology could provide meaningful uplift toward serious harm\n \n Proficiency in Python for data analysis and workflow automation\n \n Background in law enforcement, national security, defense, counterterrorism, or a relevant regulatory environment\n \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 \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 $245,000 — $330,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experienc","salary_min":245000,"salary_max":330000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["generative-ai","llm","alignment","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5410006008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-02T03:41:10Z","expires_at":"2026-11-13T16:54:56.324705Z","created_at":"2026-09-02T13:30:33.800406Z","updated_at":"2026-10-14T16:54:56.328671Z","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/51f12d71-50b2-4e11-96a7-cdac7d2c9ac2"},{"id":"907ac14b-4fcc-48ee-8292-d453378d4b94","company_id":"a0000000-0000-0000-0000-000000000001","title":"Cyber Evaluations Engineer","slug":"cyber-evaluations-engineer-5351d4ad","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 hiring Cyber Evaluations Engineers to build and run the evaluations that measure cyber-relevant capabilities and safeguard robustness in our models. You'll design new evals, run per-release robustness testing, and dig into data on jailbreaks and prompt bypasses to understand where our safeguards hold up and where they don't. You'll also design many of the probes that detect cyber abuse in production and help shape the overall detection architecture alongside the policy team. \n Key responsibilities \n \n \n Design and run capability, uplift, and safety evaluations to assess cyber-relevant risk in new models\n \n Execute per-release safeguard-robustness testing ahead of major model launches\n \n Analyze evaluation results and communicate findings clearly to the team and to stakeholders\n \n Design, prototype, and tune detection probes for cyber misuse\n \n Work with the cyber policy team to turn policy lines into a layered, robust abuse-detection architecture, and measure its precision and coverage over time\n \n Build and maintain internal tooling used to run and score evaluations\n \n Collaborate with policy and engineering partners to translate eval findings into safeguard improvements\n \n Minimum qualifications \n \n \n Experience building or running evaluations, benchmarks, or test suites for software or ML systems, including delivering results on short, fixed timelines\n \n Hands-on cybersecurity experience (e.g., CTF participation, vulnerability research, exploit development, or security research)\n \n Proficiency in Python\n \n Strong ability to communicate evaluation results with multiple cross-functional stakeholders or potential policy stakeholders\n \n Preferred qualifications \n \n \n Deep offensive-security or security-research experience, including experience building AI security benchmarks\n \n Experience analyzing adversarial or abuse data (e.g., jailbreaks, prompt bypasses, intrusion or fraud telemetry)\n \n Experience working onsite with government partners on testing or evaluation engagements\n \n Experience with AI/ML evaluation frameworks\n \n Familiarity with coordinated vulnerability disclosure practices\n \n Experience testing pre-release or pre-deployment software or models under confidentiality constraints\n \n Experience authoring detection content (e.g., Sigma, YARA, Suricata, SIEM rules) or building ML-based abuse detection\n \n Active secret security clearance or higher, or eligibility to obtain one\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 $300,000 — $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, 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,","salary_min":300000,"salary_max":405000,"location":"Washington, DC","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["security","alignment","evaluation","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5406367008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-01T21:26:36Z","expires_at":"2026-11-13T16:54:55.320955Z","created_at":"2026-09-02T13:30:16.806162Z","updated_at":"2026-10-14T16:54:55.323671Z","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/907ac14b-4fcc-48ee-8292-d453378d4b94"},{"id":"4ab10eb7-b0f8-4543-87e5-430128653c2a","company_id":"a0000000-0000-0000-0000-000000000001","title":"Safeguards Enforcement Lead, Cyber Harms","slug":"safeguards-enforcement-lead-cyber-harms-3ea20726","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 Lead, you will be responsible for managing 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 work will center on developing strategic enforcement frameworks for flagged activity related to cyberattacks, malware development, and offensive exploitation. Additionally, you will manage a team of Cyber Enforcement Analysts and contractors implementing this enforcement strategy. \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 \n Manage a team of Cyber Enforcement Analysts and contractors, overseeing the vision of Cyber Enforcement strategy \n \n Create strategies to detect and mitigate potential misuse of AI systems to facilitate cyberattacks, malware creation, exploitation tooling, and related harmful cyber operations\n \n Collaborate with stakeholders regarding novel, ambiguous, or high-severity cases\n \n Collaborate with the Safeguards Policy Design Team on policy gaps surfaced through real enforcement scenarios\n \n Partner with Engineering and Data Science teams to ensure tooling and measurement support enforcement operations.\n \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 \n Experience as a people manager\n \n Experience in cybersecurity, including knowledge of offensive techniques, exploit development, malware analysis, or vulnerability research\n \n Experience performing content review, abuse investigations, or policy enforcement at volume\n \n Proficiency in SQL and/or Python for data analysis and threat detection\n \n Experience identifying emerging risks and communicating findings to a diverse set of stakeholders, such as Product, Policy, Engineering, and Legal teams\n \n Experience working with generative AI products, including writing effective prompts for content review and enforcement\n \n Preferred qualifications\n \n \n Experience in trust \u0026 safety, abuse investigations, cybersecurity investigations, or threat intelligence in a technology or AI company\n \n Experience with large language models and an understanding of how AI technology could be misused for cyber operations\n \n Experience operating within abuse monitoring programs or enforcement review systems\n \n Understanding of the challenges involved in implementing product policies at scale, including in the content moderation space\n \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 a","salary_min":285000,"salary_max":330000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["generative-ai","security","llm","alignment","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5403775008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-29T02:52:00Z","expires_at":"2026-11-13T16:54:56.356373Z","created_at":"2026-08-29T13:30:34.116902Z","updated_at":"2026-10-14T16:54:56.359154Z","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/4ab10eb7-b0f8-4543-87e5-430128653c2a"},{"id":"414b9479-6e08-4e01-93e0-da794311a342","company_id":"a0000000-0000-0000-0000-000000000001","title":"Product Manager, Multi-Cloud Trust \u0026 Safety","slug":"product-manager-multi-cloud-trust-safety-40c195ce","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 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 A large and growing share of Claude usage reaches customers through our cloud partners — Amazon Bedrock, Google Cloud's Agent Platform, and Microsoft Foundry. These surfaces require bespoke solutions so our approaches have to be designed for third-party distribution from the start. In this role you will own how Anthropic's model safeguards, fraud defenses, and compliance posture show up on every cloud.\n Responsibilities: \n Model Safety Across Clouds \n \n Own the multi-cloud strategy and roadmap for our safeguards — data retention, automated review, human review, and enforcement — designed to fit each partner's operating model\n Design product experiences and operations paths for managing eligibility criteria, verification paths, and the controls attached to differentiated capabilities for higher-trust organizations\n Build threat-intelligence sharing with AWS, Google, and Microsoft so misuse is detected and acted on consistently across surfaces\n Drive our transparency commitments to customers and partners on data access, review, and enforcement\n \n Fraud \u0026 Abuse \n \n Own fraud and abuse defenses for partner-sold offerings: bot and mass-registration abuse, pre- and post-sale risk controls, and chargebacks where the partner owns billing\n Define the fraud signals we exchange with each cloud partner and turn them into product requirements that influence growth initiatives \n \n Cross-functional Leadership \n \n Engage directly with enterprise security, risk, and compliance leaders to understand their requirements and turn them into roadmap priorities\n Be Anthropic's product counterpart to trust \u0026 safety, security, and compliance teams at AWS, Google, and Microsoft\n Work with Safeguards, Inference, Policy, Security, Legal, and multi-cloud engineering to ship one coherent set of controls across three clouds\n Partner with sales and partnerships to support enterprise evaluations where data-handling and safety requirements are decisive\n Work with marketing and partner teams on how we position our safeguards externally\n \n  \n Minimum requirements: \n \n Have 10+ years of experience.\n Have 5+ years of product experience in platform product roles on high-scale, enterprise- or developer-facing software.\n Operate with high autonomy in ambiguous, fast-moving environments, with a track record of executing across teams and organizations.\n Are an excellent written communicator and able to drive clarity out of complexity.\n Are equally fluent in policy nuance and systems detail, and can explain the tradeoff between them to lawyers, engineers, go to market teams, and partner executives alike.\n \n Preferred requirements \n \n Prior product experience in trust \u0026 safety, security, privacy, or compliance.\n Have built or shipped products with a hyper-scaler as a partner — you know how to align strategic goals and deliver impact over multiple quarters in partnership with an external third party \n Have owned a top line revenue target while being held to counter-risk outcome — a fraud-loss number, an abuse rate, a compliance authorization, an enforcement program — not just a product roadmap.\n Direct experience on a trust \u0026 safety, fraud, or security product team at AWS, GCP, or Azure — or at an ISV that ships through one of their marketplaces.\n Background in AI safety, content moderation, or abuse-detection systems.\n Designed incident-response or escalation processes that span more than one company.\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 $305,000 — $385,000 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 o","salary_min":305000,"salary_max":385000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["cloud","payments","alignment","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5409934008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T22:04:00Z","expires_at":"2026-11-13T16:54:56.002575Z","created_at":"2026-08-29T13:30:27.591482Z","updated_at":"2026-10-14T16:54:56.005369Z","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/414b9479-6e08-4e01-93e0-da794311a342"},{"id":"8f5683c8-4601-44f3-ae28-99878029e10f","company_id":"a0000000-0000-0000-0000-000000000001","title":"Head of Policy Design, Societal Harms","slug":"head-of-policy-design-societal-harms-25b5c82a","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 organization builds the policies, evaluations, and detection and enforcement systems that define and hold the limits on how Claude can be used. In this role, you'll lead our policy design team, managing the teams responsible for radicalization, child safety, user well-being, harmful manipulation, and election integrity, among other harm areas.\n The team is responsible for understanding and defining the risks that come with engaging with Claude, how those risks materialize in the real world, and the mitigations needed to prevent them. As the manager, you'll work with your team to draw the boundaries between what is and is not allowed, then partner with research, product, and engineering to build the right interventions. Mitigating these harms takes the whole stack: the values and judgment trained into the model itself, the policies and detection systems we enforce on top of it, and the interventions we build into our products. More capable models, new product surfaces, and new user behaviors will keep testing these boundaries, so the team's policies have to keep pace.\n You'll work closely with product to develop and iterate on the strategy and vision for how our safety layers fit together, and with your team and cross-functional partners to decide which mitigations make the most sense and how to implement them. You'll also coordinate policy decisions across the portfolio: ensuring they're made with the right stakeholders in the room, tracked over time, and applied consistently across harm areas and product surfaces.\n This is a leadership role for someone who combines expertise in the harm areas themselves with fluency in how frontier models are actually developed and deployed, and who does their best work across team boundaries. You'll spend as much time developing the leads who own each harm area as you will on the policy questions themselves.\n *Important context for this role: some of the work involves exposure to explicit content, including material of a sexual, violent, or psychologically disturbing nature.\n Key responsibilities \n \n \n Lead, develop, and grow the managers and teams responsible for the consumer harms portfolio, including child safety, user well-being, harmful manipulation, and election integrity\n \n Coordinate policy decisions across the portfolio, and build the mechanisms that keep them tracked, consistent, and legible — so stakeholders know what was decided, why, and who owns what\n \n Set the strategy for how mitigations built on top of the model — policies, detection and enforcement systems, and product interventions — complement what is trained into the model itself, partnering closely with the alignment training team that owns Claude's character\n \n Prioritize across harm areas competing for the same resources, and make those tradeoffs and their rationale clear to leadership\n \n Serve as the escalation point for high-severity and ambiguous consumer harms decisions, including rapid response to emerging risks\n \n Partner with engineering, data science, product, legal, and research across the model development cycle so consumer harms considerations are represented from training through launch, on every surface where Claude is deployed\n \n Engage external experts, civil society organizations, and regulators, and translate that engagement into stronger policy and enforcement\n \n Minimum qualifications \n \n \n Experience leading teams — including managing managers or senior specialists — in AI safety, product policy, or a related field\n \n Deep, applied familiarity with consumer harm areas such as child safety, mental health and well-being, manipulation, or election integrity, and good judgment about how these harms differ in mechanism, severity, and mitigation\n \n A track record of exceptional cross-team collaboration: building durable working relationships with teams you don't control, and getting to shared decisions where ownership is genuinely distributed\n \n Working understanding of how frontier models are developed and deployed — the training and fine-tuning cycle, evaluations, and launch processes — and how different model environments (consumer products, APIs, agentic tools) change both risk and the mitigations available\n \n Experience translating policy positions into mechanisms that can be enforced and measured, and communicating the reasoning to technical and non-technical audiences, including executives\n \n Sound judgment in ambiguous, high-consequence decisions, and comfort making a call and escalating appropriately on incomplete information\n \n Preferred qualifications \n \n \n Subject-matter depth in one","salary_min":330000,"salary_max":395000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["alignment","agents","fine-tuning","generative-ai","llm","healthcare","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5407418008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T19:56:10Z","expires_at":"2026-11-13T16:54:55.694701Z","created_at":"2026-08-29T13:30:22.347939Z","updated_at":"2026-10-14T16:54:55.697549Z","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/8f5683c8-4601-44f3-ae28-99878029e10f"},{"id":"c50734fd-508c-406a-bf60-d6bee6e444b5","company_id":"a0000000-0000-0000-0000-000000000001","title":"Policy Design Manager, Conventional Weapons","slug":"policy-design-manager-conventional-weapons-7a320e38","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 organization builds the policies, evaluations, and enforcement systems that define and hold the limits on how Claude can be used. In this role, you'll own our conventional weapons work.\n Defining a crisp boundary between acceptable and harmful requests in this domain is difficult, because the underlying components are dual-use: the same capabilities that serve civilian engineering and research can also contribute to a weapons system. Building the threat models, evaluations, and detection systems that hold that boundary is the core of this role.\n Conventional weapons are increasingly defined by software, and the risks reach well beyond firearms: from a model operating a weapons system or writing guidance code, to the weaponization of dual-use platforms. The role spans every weapon class, up to autonomous systems that select and engage targets without human authorization.\n You will help define the line between prohibited weapons development and legitimate research and engineering work, and how to operationalize the distinction. This will include translating technical judgment into principles that engineers can implement and enforcement teams can act on.\n Key responsibilities\n \n \n Own and maintain Anthropic's conventional weapons policy, defining the boundary between the activities our models should and should not support\n \n Build the threat models and evaluations that measure how our models could contribute to weapons development, including the software and autonomy components that define modern weapons systems, and keep them current as the technology and its misuse evolve\n \n Partner with engineering to turn the policy into model guardrails, detection systems, and enforcement tooling\n \n Serve as the subject-matter expert for escalations involving conventional weapons content, including rapid response to emerging risks\n \n Build shared understanding of the policy across product, engineering, legal, and leadership, communicating its reasoning to technical and non-technical audiences\n \n Engage external experts as well as government and industry partners, and translate that engagement into stronger policy and enforcement\n \n Minimum qualifications\n \n \n Have deep, applied expertise in weapons systems and can translate complex technical evidence into sound policy judgments\n \n Experience in a relevant setting, such as a service research laboratory, a defense research or innovation agency, or a company that designs or builds weapons systems\n \n Can write clear, operationally precise policy and explain complex technical topics to non-specialist audiences\n \n Understand the legal frameworks governing weapons and their transfer, and can craft policy that holds up across jurisdictions\n \n Can do rigorous technical analysis of weapons systems using only open sources\n \n Are comfortable with ambiguity and drawn to problems that have no established playbook\n \n Are motivated by preventing misuse without obstructing the legitimate work in the field\n \n Preferred qualifications\n \n \n A working understanding of machine learning and large language model fundamentals\n \n Hands-on engineering experience in a weapons-relevant technical domain, such as systems engineering, robotics and autonomy, guidance/navigation/control, sensors and signal processing, aerospace or mechanical engineering, materials and energetics, or embedded software\n \n Hands-on experience applying arms export controls (ITAR/EAR) or international arms-control regimes\n \n Experience building or evaluating classifiers, including LLM-based ones, and reasoning about precision and recall for rare, high-consequence categories\n \n Trust \u0026 safety or product policy experience at a technology platform\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 ","salary_min":245000,"salary_max":285000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["robotics","alignment","llm","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5392184008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-22T03:46:05Z","expires_at":"2026-11-13T16:54:55.94206Z","created_at":"2026-08-25T18:26:14.591016Z","updated_at":"2026-10-14T16:54:55.94479Z","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/c50734fd-508c-406a-bf60-d6bee6e444b5"},{"id":"0de3bf04-c0e7-4cad-808a-3b266b247482","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"MSE, Vehicle Software, RUST","slug":"mse-vehicle-software-rust-6adc91e9","description":"Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n ABOUT THE TEAM \n Air Dominance \u0026 Strike (AD\u0026S) is responsible for autonomous robotics systems like the Fury unmanned fighter jet and the Barracuda family of advanced effects. The AD\u0026S Vehicle Software team is responsible for the software running on these systems. Our senior software engineers collaborate with other engineering disciplines to develop software for vehicle control, networking, sensor integration, and telemetry. We are looking for engineers excited to build the foundational vehicle software stack that supports the wide range of AD\u0026S initiatives, from early concept simulation to first flight to live operations to large scale fleet management.\n REQUIRED QUALIFICATIONS \n \n Eligible to obtain and maintain an active U.S. Top Secret security clearance\n BS, MS, or PhD in Computer Science, Software Engineering, Mathematics, Physics, or related field.\n 3+ years of production-grade Rust and/or C++ experience in a Linux development environment\n Experience building software solutions involving significant amounts of data processing and analysis\n Ability to quickly understand and navigate complex systems and established code bases\n A desire to work on critical software that has a real-world impact\n Travel up to 20% of time to build, test, and deploy capabilities in the real world\n \n PREFERRED QUALIFICATIONS \n \n Strong background with focus in Physics, Mathematics, and/or Motion Planning to inform modeling \u0026 simulation (M\u0026S) and physical systems\n Developing and testing multi-agent autonomous systems and deploying in real-world environments.\n Feature and algorithm development with an understanding of behavior trees.\n Developing software/hardware for flight systems and safety critical functionality.\n Distributed communication networks and message standards\n Knowledge of military systems and operational tactics\n US Salary Range\n $166,000 — $220,000 USD \n The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:   \n  \n Benefits \n At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next.  For more information, Explore Our Benefits . \n  \n \n Protecting Yourself from Recruitment Scams \n Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates. We've observed a rise in sophisticated phishing and fraudulent schemes where individuals impersonate Anduril representatives, luring job seekers with false interviews or job offers. These scammers often attempt to extract payment or sensitive personal information.\n \n To ensure your safety and help you navigate your job search with confidence, please keep the following critical points in mind:\n \n \n No Financial Requests:  Anduril will never solicit payment or demand personal financial details (such as banking information, credit card numbers, or social security numbers) at any stage of our hiring process. Our legitimate recruitment is entirely free for candidates.\n Please always verify communications: \n \n Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an @anduril.com address.\n Via Agency Partner: If contacted by a recruiting agency for an Anduril role, their email will clearly identify their agency. If you suspect any suspicious activity, please verify the agency's authenticity by reaching out to contact@anduril.com . \n \n \n Exercise Caution with Unsolicited Outreach:  If you receive any communication that appears suspicious, contains grammatical errors, or makes unusual requests, do not engage. Always confirm the sender's email domain is @anduril.com before providing any personal information or clicking on links.\n \n What to Do If You Suspect Fraud:  Should you ","salary_min":166000,"salary_max":220000,"location":"Costa Mesa, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["agents","cloud","gpu","payments","robotics","computer-vision","rust"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5218934007?gh_jid=5218934007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-21T19:48:46Z","expires_at":"2026-11-13T16:57:16.015536Z","created_at":"2026-08-25T18:28:19.086086Z","updated_at":"2026-10-14T16:57:16.018608Z","company_name":"Anduril","company_slug":"anduril","company_logo_url":"https://www.google.com/s2/favicons?domain=anduril.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0de3bf04-c0e7-4cad-808a-3b266b247482"},{"id":"101f37b3-5ed1-4260-9a90-3f56237af448","company_id":"3029e985-56bf-4ac2-9ae1-df4cdd53b12f","title":"Staff Software Engineer - AI Security (Go/Rust/Python)","slug":"staff-software-development-engineer-76db063f","description":"Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 200+ public data centers globally and thousands of private sites at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform.\n We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler.\n \n Role  \n We are looking for a Staff Software Engineer - AI Security to join our team. This is a Hybrid role based in San Jose, CA, reporting to the Director, Software Engineering  in the Engineering department. We are building security products that enable organizations to adopt AI applications and agents safely and at scale. As a Staff Software Engineer, you will take ownership of complex engineering challenges, build secure and scalable systems, and raise the technical bar through hands-on execution and collaboration.\n What you’ll do (Role Expectations) \n \n Define technical direction and architecture for major areas of the product\n Lead high-impact initiatives that span multiple teams and system boundaries\n Turn ambiguous product and security challenges into clear, executable engineering strategies\n Establish standards for secure, reliable, scalable, and maintainable systems\n Identify systemic risks, architectural gaps, and investments needed for long-term growth\n \n Who You Are (Success Profile) \n \n You thrive in ambiguity. You build the path as you walk it, viewing ambiguity not as a hindrance but as raw material to create impactful solutions.\n You act like an owner. Your passion for the mission fuels your bias for action, seamlessly navigating between high-level strategy and hands-on execution.\n You are a problem-solver. You are energized by complex challenges and finding elegant solutions that deliver maximum value.\n You are a high-trust collaborator. You build strong relationships through clear feedback, respect, and a commitment to team success.\n You are driven by innovation. You possess a deep curiosity for how systems work and are energized by solving technical challenges at the cutting edge of AI security.\n \n What We’re Looking for (Minimum Qualifications) \n \n Demonstrated curiosity and active exploration of AI tools, with a proven history of integrating new technologies to enhance daily workflows and augment problem-solving\n 5+ years of software-engineering experience, including technical leadership across complex production systems\n Strong proficiency in Go, Rust, and Python, with deep expertise in systems engineering, security engineering, and backend platforms\n Demonstrated experience architecting and evolving platforms that span multiple teams or product areas\n Proven ability to remain hands-on through coding, prototyping, design review, and complex debugging\n Deep understanding of concurrency, networking, storage, APIs, data systems, and cloud infrastructure on AWS, GCP, or Azure\n \n What Will Make You Stand Out (Preferred Qualifications) \n \n Experience building enterprise security, endpoint, cloud, or infrastructure products\n Familiarity with AI/ML systems, analytics platforms, AI applications, or AI security\n Experience helping a startup or high-growth product evolve into a scalable engineering organization\n \n #LI-YC2 #LI-Hybrid\n Zscaler’s salary ranges are benchmarked and are determined by role and level. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations and could be higher or lower based on a multitude of factors, including job-related skills, experience, and relevant education or training.\n The base salary range listed for this full-time position excludes commission/ bonus/ equity (if applicable) + benefits.\n Base Pay Range\n $152,000 — $190,000 USD \n At Zscaler, we are committed to building a team that reflects the communities we serve and the customers we work with. We foster an inclusive environment that values all backgrounds and perspectives, emphasizing collaboration and belonging. Join us in our mission to make doing business seamless and secure.\n Our Benefits program is one of the most important ways we support our employees. Zscaler proudly offers comprehensive and inclusive benefits to meet the diverse needs of our employees an","salary_min":152000,"salary_max":190000,"location":"San Jose, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["security","fine-tuning","cloud","rust","python"],"apply_url":"https://job-boards.greenhouse.io/zscaler/jobs/5202464007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-17T22:18:48Z","expires_at":"2026-11-13T16:58:15.633012Z","created_at":"2026-08-25T18:29:23.045838Z","updated_at":"2026-10-14T16:58:15.636656Z","company_name":"Zscaler","company_slug":"zscaler","company_logo_url":"https://www.google.com/s2/favicons?domain=zscaler.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/101f37b3-5ed1-4260-9a90-3f56237af448"},{"id":"47f0e382-b011-49ee-a450-b151364fed77","company_id":"f5ee7284-a657-4da2-b351-cb806a3681cd","title":"Software Engineer - Platform Infrastructure (Rust, C++)","slug":"software-engineer-platform-infrastructure-rust-c-8231bc6c","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 making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.\n RESPONSIBILITIES: \n \n Design, build, and implement a large-scale distributed system that powers one of the world's largest supercomputing clusters.\n Dive into the low-level stack to profile, debug, and optimize performance across diverse systems, including GPUs, Linux kernel, networking, and filesystems, to achieve peak efficiency.\n Collaborate on hardware, software, and algorithm co-design to push the boundaries of AI training.\n Maintain and innovate on our codebase to ensure scalability and reliability.\n Develop tools to enhance team productivity and streamline workflows.\n \n BASIC QUALIFICATIONS: \n \n Systems programming experience in C, C++, or Rust\n Computer systems fundamentals with a grasp of how computers execute code from transistors to high-level applications.\n Hands-on expertise with Kubernetes (K8s), including cluster architecture, pod lifecycle, networking (CNI), storage (CSI), service mesh, and production-grade operations\n \n PREFERRED SKILLS AND EXPERIENCE: \n \n Collaborate in a fast-paced, open environment to design and foundational systems.\n Strong debugging skills across the full stack — from kernel and OS up through container orchestration layers\n Deep knowledge of operating systems internals (process scheduling, memory management, file systems, and synchronization primitives)\n Proficiency in performance analysis, profiling, and low-level optimization techniques\n Solid understanding of computer networks and the TCP/IP stack\n Experience working with Linux kernel concepts or systems-level debugging tools (e.g., perf, gdb, strace, Wireshark)\n Proficiency deploying and managing workloads using Kubernetes manifests, Helm, Operators, and GitOps workflows\n Solid understanding of containerization technologies (Docker, containerd, crio) and their interaction with the Linux kernel\n Experience with observability and monitoring in distributed systems (Prometheus, Grafana, VictoriaMetrics, OpenTelemetry, or similar)\n \n COMPENSATION AND BENEFITS: \n $180,000 - $440,000 USD\n Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short \u0026 long-term disability insurance, life insurance, and various other discounts and perks.\n SpaceXSI is an equal opportunity employer. For details on data processing, view our  Recruitment Privacy Notice .","salary_min":180000,"salary_max":440000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["distributed-systems","rust","infrastructure","c++"],"apply_url":"https://job-boards.greenhouse.io/xai/jobs/5191142007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-20T19:48:01Z","expires_at":"2026-11-13T16:55:31.900651Z","created_at":"2026-07-22T14:03:42.893161Z","updated_at":"2026-10-14T16:55:31.903329Z","company_name":"xAI","company_slug":"xai","company_logo_url":"https://www.google.com/s2/favicons?domain=x.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/47f0e382-b011-49ee-a450-b151364fed77"},{"id":"2f5351d0-9726-4e50-85f8-0f191d743846","company_id":"0a7c68cd-f294-457e-939a-62969b72e929","title":"Software Engineer, Distributed Systems - Trust \u0026 Safety","slug":"software-engineer-distributed-systems-trust-safety-9cb368dc","description":"WHY THIS ROLE MATTERS NOW\n\nAI has dramatically lowered the barrier for bad actors. Generating convincing phishing pages, spinning up realistic-looking fraudulent accounts, and producing abusive content at scale no longer requires specialized skill — a motivated attacker with access to widely available models can do it. \n\nAt the same time, AI is transforming what's possible on the defensive side. A small, sharp T\u0026S team equipped with frontier models can now build detection, triage, and response systems that would have required a team five times the size just a couple of years ago. AI-assisted content scanning, automated investigation workflows, and intelligent alert prioritization mean that a lean team can protect millions of users — if they build the right infrastructure.\n\n\n\n\nABOUT THE ROLE\n\nYou'll architect and scale the trust infrastructure that keeps 70M+ users safe while preserving the creative freedom that makes Gamma magical. This means designing distributed systems for real-time content scanning, anomaly detection, and rate limiting; helping define and evolve the core data model and storage systems behind abuse detection; and shipping the high-volume event pipelines and internal tools that let our support teams act quickly on threats.\n\nYou'll join a small, high-impact team building the foundation for trust at scale. You'll work across databases, public APIs, and event infrastructure, balancing long-term technical investments with rapid shipping velocity. You'll collaborate across engineering, product, and design to define how Gamma approaches safety for the long term.\n\nOur team has a strong in-office culture and works in person 4–5 days per week in San Francisco. We love working together to stay creative and connected, with flexibility to work from home when focus matters most.\n\n\n\n\nWHAT YOU'LL DO\n\n - Own detection and prevention systems for fraud, abuse, spam, and malicious content across millions of daily users\n\n - Design and build scalable trust infrastructure including rate limiting, content scanning, anomaly detection, and account security\n\n - Architect distributed systems, APIs, and high-volume event pipelines that power real-time abuse detection at Gamma's scale\n\n - Help define and evolve the core data model and storage systems that underpin trust and safety across the product\n\n - Build tools that empower internal support teams to investigate and act on suspicious or malicious activity\n\n - Leverage AI/LLM-based detection to stay ahead of AI-generated abuse — phishing, fraud, and malicious content that's increasingly indistinguishable from legitimate activity\n\n - Build automated triage and investigation workflows that let a small team operate at the scale of a much larger one\n\n - Investigate and resolve complex security incidents with limited context\n\n - Partner with engineering and product to balance security with user experience\n\n - Shape Gamma's long-term trust and safety strategy and technical roadmap\n\n\n\n\nWHAT YOU'LL BRING\n\n - 5+ years of backend engineering experience building scalable, high-traffic production systems\n\n - Strong systems thinking and experience building highly available web APIs\n\n - Strong proficiency in backend technologies (Node.js, Python, or similar) and databases (PostgreSQL, Redis)\n\n - Experience with event streaming systems (Redis, Kafka, or similar) and high-volume event pipelines\n\n - Hands-on experience implementing trust features like rate limiting, content detection, and fraud prevention\n\n - Track record shipping high-quality, complex applications under tight timelines\n\n - Product-minded approach with understanding of how technical decisions impact user experience and business metrics\n\n - Passion for security, user protection, and solving problems at scale\n\nNice to have\n\n - Experience with AI/LLMs for content moderation, or familiarity with TypeScript, Prisma, Apollo GraphQL, or AWS\n\n - Experience building AI-assisted moderation pipelines or using frontier models for automated abuse detection and response\n\n - Familiarity with the evolving AI threat landscape — how generative models are being used for phishing, social engineering, and content abuse at scale\n\n - Experience with real-time collaboration systems\n\n\n\n\nCOMPENSATION RANGE:\n\nThe base salary for this full-time position, which spans multiple internal levels depending on qualifications, ranges between $180K–$310K plus benefits \u0026 equity.\n\n\n\nFinal offer amounts are determined by multiple factors, including but not limited to experience and expertise in the requirements listed above.\n\n\n\nIf you're interested in this role but you don't meet every requirement, we encourage you to apply anyway! We're always excited about meeting great people.","salary_min":180000,"salary_max":310000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["distributed-systems","llm","api-design","rust"],"apply_url":"https://jobs.ashbyhq.com/gamma/1d76bf68-c948-4594-a6f5-b836eaf33c4b/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-15T22:52:49.328Z","expires_at":"2026-11-13T16:57:31.001592Z","created_at":"2026-07-16T14:08:43.739411Z","updated_at":"2026-10-14T16:57:31.005148Z","company_name":"Gamma","company_slug":"gamma","company_logo_url":"https://www.google.com/s2/favicons?domain=gamma.app\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/2f5351d0-9726-4e50-85f8-0f191d743846"},{"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":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["security","llm","generative-ai","alignment","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":"2026-11-13T16:54:56.336007Z","created_at":"2026-07-12T14:00:28.485977Z","updated_at":"2026-10-14T16:54:56.338974Z","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":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["alignment","generative-ai","llm","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":"2026-11-13T16:54:56.342381Z","created_at":"2026-07-12T14:00:28.575559Z","updated_at":"2026-10-14T16:54:56.349314Z","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"}],"page":1,"per_page":20,"total":74,"total_is_exact":true,"total_pages":4}