{"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":"74bd7349-e7f3-4d98-a3f0-ba2a67cb91ec","company_id":"a0000000-0000-0000-0000-000000000001","title":"Director, Finance Systems - Revenue Systems Engineering","slug":"director-finance-systems-revenue-systems-engineering-0b4e7d9d","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role \n We are seeking an experienced Revenue Systems Engineering Director to join our Finance Systems team at Anthropic. You will own the technical architecture, implementation, and optimization of our Order-to-Cash (OTC) systems as we scale globally. You'll serve as the technical lead for our revenue systems within the ERP ecosystem, driving automation of revenue recognition processes and integrating our billing, sales, and financial systems.\n Responsibilities \n Revenue Platform Architecture \u0026 Development \n \n \n Own the revenue systems architecture and development supporting multi-entity operations and global subsidiaries\n \n Design and implement scalable data pipelines using DBT/SQL frameworks to transform high-volume financial transactions with low-latency response times for real-time integrations\n \n Build and maintain automated revenue recognition workflows ensuring ASC 606 compliance for complex subscription and consumption-based billing models\n \n Data Engineering \u0026 Pipeline Orchestration \n \n \n Modify, enhance, and optimize data transformation models using DBT/SQL to support standardized data flows across accounting, billing engineering, and product teams\n \n Establish comprehensive testing frameworks for data transformations, formally documenting successful behavior to support System Integration Testing (SIT) and audit requirements\n \n Systems Integration \u0026 Technical Leadership \n \n \n Collaborate with Revenue Accounting, Data Infrastructure, and BizTech teams to design enterprise-grade integration patterns supporting significant transaction volume growth\n \n Implement automated reconciliation engines achieving rapid variance detection and substantially reducing manual revenue team effort\n \n Provide technical expertise during month-end close processes, ensuring system reliability and performance during peak transaction volumes\n \n Innovation \u0026 Continuous Improvement \n \n \n Pioneer AI integration for revenue operations, building intelligent agents for discrepancy investigation, automated testing, and self-service analytics\n \n Evaluate and implement emerging technologies to modernize integration architecture\n \n Establish best practices with CI/CD pipelines, automated testing, and deployment workflows maintaining high reliability standards\n \n Mentor team members on technical best practices, code reviews, and documentation standards\n \n Minimum qualifications \n \n \n Possess strong technical proficiency in Python, SQL, DBT, and modern data engineering tools (workflow orchestration, infrastructure as code, cloud data warehouses)\n \n Have extensive experience with enterprise billing platforms and revenue recognition requirements (ASC 606)\n \n Demonstrate expert-level understanding of ERP systems with hands-on configuration and integration experience, including proficiency with API development (REST, SOAP/XML, webhooks) and understanding of ERP extension patterns and custom object development\n \n Experience with additional programming languages (Java, JavaScript/TypeScript, Go) for building integrations, APIs, and custom ERP extensions\n \n Track record of leading technical workstreams during ERP transformations or major system migrations\n \n Are skilled at designing scalable integration architectures, including both real-time APIs and batch processing patterns for high-volume financial transactions\n \n Have proven ability to translate complex business requirements into robust technical solutions while maintaining alignment with accounting principles and audit standards\n \n Understanding of consumption-based pricing models, usage metering platforms, and marketplace billing\n \n Thrive in a fast-paced, high-growth environment where you'll balance innovation with operational stability\n \n Have excellent communication skills to bridge technical and business stakeholders, including Finance, Accounting, Revenue Operations, and Engineering teams\n \n Preferred qualifications \n \n Have 12+ years of experience in revenue systems engineering, with deep hands-on expertise in Order-to-Cash (OTC) implementations\n \n \n \n Experience implementing revenue platforms at scale for SaaS or subscription-based businesses processing high transaction volumes\n \n Background in financial systems implementations supporting multi-entity, multi-currency operations with complex revenue recognition scenarios\n \n Hands-on experience with CRM/CPQ platforms and integration patterns connecting sales systems to billing and ERP systems\n \n Specific experience with: Salesforce CPQ/Revenue Cloud, Zuora, Stripe Billing,, Workday Financials\n \n Familiarity with Workday Prism and Oracle Accounting Hub solutions for managing third-par","salary_min":270000,"salary_max":315000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["agents","payments","llm","alignment","data-pipeline","api-design"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5409055008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-29T06:34:37Z","expires_at":"2026-09-28T13:30:18.093747Z","created_at":"2026-08-29T13:30:18.244908Z","updated_at":"2026-08-29T13:30:18.244908Z","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/74bd7349-e7f3-4d98-a3f0-ba2a67cb91ec"},{"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":"Washington, DC","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","security","alignment","generative-ai","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":"2026-09-28T13:30:33.964118Z","created_at":"2026-08-29T13:30:34.116902Z","updated_at":"2026-08-29T13:30:34.116902Z","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":["alignment","payments","cloud","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":"2026-09-28T13:30:27.442837Z","created_at":"2026-08-29T13:30:27.591482Z","updated_at":"2026-08-29T13:30:27.591482Z","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":"ac9a7cfe-0d87-46a1-9a22-dc3d0f92e813","company_id":"12105b3e-eb1d-4a92-95b6-855042facaf1","title":"Senior Product Manager - Core AI (Understand)","slug":"senior-product-manager-core-ai-understand-795d69c4","description":"At Qualtrics, we create software the world’s best brands use to deliver exceptional frontline experiences, build high-performing teams, and design products people love. But we are more than a platform—we are the creators and stewards of the Experience Management category serving over 18K clients globally. Building a category takes grit, determination, and a disdain for convention—but most of all it requires close-knit, high-functioning teams with an unwavering dedication to serving our customers.\n When you join one of our teams, you’ll be part of a nimble group that’s empowered to set aggressive goals and move fast to achieve them. Strategic risks are encouraged and complex problems are solved together, by passing the mic and iterating until the best solution comes to light. You won’t have to look to find growth opportunities—ready or not, they’ll find you. From retail to government to healthcare, we’re on a mission to bring humanity, connection, and empathy back to business. Join over 5,000 people across the globe who think that’s work worth doing.\n Senior Product Manager, Core AI (Understand) \n Why We Have This Role \n \n Define the future of Qualtrics' Understand layer — the intelligence that turns raw experience data into structured meaning, prediction, and insight across the entire portfolio.\n Own the product strategy for the capabilities that let AI systems and product teams reason about experience data: ontologies and semantic systems, text analytics enrichments, prediction, simulation, and benchmarking.\n Own the Core AI platform foundations that these capabilities depend on: agent infrastructure, context and memory, tools and orchestration, agent evaluation, observability, and AI safety.\n Manage the entire lifecycle for multiple functional areas of Understand, from framing the problem, to aligning on architecture and product direction, to forming the plan, delivering implementation, and iterating until the capabilities are world-class.\n \n How You'll Find Success \n \n Partner with product, engineering, data science, research, and design teams across Qualtrics to understand what enrichment, modeling, and platform capabilities they need to build exceptional AI products.\n Develop a deep understanding of the needs of both enterprise customers and internal AI product builders, and translate those needs into strategy, requirements, and roadmaps.\n Define product strategy across the Understand surface area: ontologies and semantic layers, text analytics and enrichment pipelines, predictive models, simulation, benchmarking, and the agent runtime, orchestration, memory, evaluation, and guardrail capabilities that support them.\n Prioritize investments based on customer value, insight quality, developer productivity, technical leverage, reuse across Qualtrics products, and opportunities for competitive differentiation.\n Collaborate deeply with engineering, AI research, and data science teams to make thoughtful product and architectural tradeoffs in a rapidly evolving technical landscape.\n Develop clear frameworks for evaluating the quality, accuracy, reliability, safety, and business impact of enrichment models, predictive systems, and agentic AI.\n Build the benchmarking discipline that lets Qualtrics prove its models and enrichments are better than alternatives — internally and to customers.\n Create shared capabilities that accelerate AI development across Qualtrics while providing the reliability, governance, security, and observability required by enterprise customers.\n Develop and communicate a compelling vision and roadmap to senior leaders, product teams, technical stakeholders, and customers.\n Define and monitor meaningful KPIs for adoption, model and enrichment quality, prediction accuracy, evaluation performance, developer velocity, reliability, and customer impact.\n Stay at the forefront of developments in foundation models, agents, evaluation methods, semantic systems, causal and predictive modeling, simulation, and enterprise AI infrastructure — and translate them into concrete product opportunities.\n \n How You'll Grow \n \n By shaping the technical and product foundations for how Qualtrics understands experience data.\n Through developing deep expertise across ontologies, semantic systems, text analytics, prediction, simulation, benchmarking, agent architecture, and evaluation.\n By making high-leverage product decisions that influence multiple product lines and teams.\n Through leading complex, ambiguous initiatives that require alignment across product, engineering, research, data science, security, and go-to-market organizations.\n By developing your ability to connect rapidly evolving AI technologies to durable customer value and differentiated product strategy.\n \n Things You'll Do \n \n Develop and execute the product strategy for Qualtrics' Understand layer.\n Define the foundational architecture and capabilities required for teams across Qualtrics to build reliable, differentiat","salary_min":166500,"salary_max":218500,"location":"Seattle, WA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","healthcare","alignment","generative-ai","nlp","llm"],"apply_url":"https://www.qualtrics.com/careers/us/en/job/8164973?gh_jid=8164973","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T21:33:55Z","expires_at":"2026-09-28T13:50:43.79313Z","created_at":"2026-08-29T13:50:43.963199Z","updated_at":"2026-08-29T13:50:43.963199Z","company_name":"Qualtrics","company_slug":"qualtrics","company_logo_url":"https://www.google.com/s2/favicons?domain=qualtrics.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/ac9a7cfe-0d87-46a1-9a22-dc3d0f92e813"},{"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":["fine-tuning","alignment","agents","llm","generative-ai","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":"2026-09-28T13:30:22.194296Z","created_at":"2026-08-29T13:30:22.347939Z","updated_at":"2026-08-29T13:30:22.347939Z","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":"1edaacf5-142d-4d7d-bca8-60df2de49655","company_id":"fe4d898e-86f1-400e-95db-988d7f632620","title":"Sr. Software Engineer, AI","slug":"sr-software-engineer-ai-29348a1b","description":"Navan is building the next generation of intelligent travel experiences, where loyalty, personalization, and AI agents help travelers make better decisions before, during, and after every trip. As a Senior Software Engineer, AI on the Loyalty Wallet team, you’ll build agentic product experiences that understand a traveler’s loyalty programs, surface useful insights, and safely help users manage their memberships through Navan Edge.\n What You’ll Do: \n \n Build AI-Powered Product Experiences: Design and develop agentic workflows that help users view, understand, connect, and manage their loyalty programs through chat, wallet surfaces, and personalized recommendations.\n Develop Production AI Systems: Build reliable LLM-powered flows with structured outputs, tool calling, guardrails, human confirmation, evals, and monitoring for real customer-facing use cases.\n Own Agent and Workflow Quality: Create and maintain scenario tests, adversarial evals, prompt/tool contracts, and quality metrics that ensure agents behave safely around loyalty data, PII, financial guidance, and unsupported requests.\n Integrate Across the Stack: Work across frontend, backend, and AI orchestration layers, including wallet APIs, streaming chat experiences, UI components, data services, and ML/LLM workflows.\n Turn Data Into Personalization: Help transform loyalty balances, tier progress, membership data, connected email signals, and trip context into useful recommendations and next-best actions.\n Collaborate Cross-Functionally: Partner closely with product, design, backend, data, and platform teams to ship polished, measurable customer experiences.\n Raise the Engineering Bar: Champion maintainable code, thoughtful abstractions, strong tests, observability, documentation, and operational ownership.\n \n What We’re Looking For: \n \n 6+ years of software engineering experience building production systems, with meaningful hands-on experience in AI, LLM, agent, workflow, or ML-powered products.\n Experience building agentic systems, tool-calling workflows, RAG-like systems, structured LLM outputs, eval pipelines, or AI assistants in production.\n Strong engineering fundamentals in TypeScript/Node.js, Java, Python, or similar backend/product engineering stacks.\n Experience with distributed systems, APIs, async workflows, caching, observability, and production debugging.\n Comfort working with AI safety patterns such as guardrails, HITL confirmation, deterministic tool boundaries, hallucination prevention, and PII-sensitive workflows.\n Product mindset and ability to translate ambiguous user needs into robust, user-facing experiences.\n Strong ownership mentality, with the ability to ship, measure, iterate, and support features after release.\n Experience with travel, loyalty programs, personalization, fintech, or consumer data products is a strong plus.\n Bachelor’s or Master’s degree in Computer Science, Engineering, or related field, or equivalent hands-on experience.\n \n  \n The posted pay range represents the anticipated low and high end of the compensation for this position and is subject to change based on business need. To determine a successful candidate’s starting pay, we carefully consider a variety of factors, including primary work location, an evaluation of the candidate’s skills and experience, market demands, and internal parity. For roles with on-target-earnings (OTE), the pay range includes both base salary and target incentive compensation. Target incentive compensation for some roles may include a ramping draw period. Compensation is higher for those who exceed targets. Candidates may receive more information from the recruiter.\n Pay Range\n $113,400 — $252,000 USD \n  \n Navan uses AI-assisted Automated Employment Decision Tool (Metaview) to assist with evaluating resumes against job qualifications for this role. All final decisions are made by human recruiters and hiring managers. \n Human oversight:   Metaview does not automatically reject candidates or make final hiring decisions. Our recruiters and hiring managers review all outputs and make the final hiring decision regarding every application.  \n \n \n Your rights: If you prefer to have your application reviewed without AI assistance, you may request a human evaluation by entering your email here . Your decision to do so will not affect how your candidacy is evaluated. \n \n Please refer to our Candidate Privacy Notice for more information about our processing of personal data, and your rights.","salary_min":113400,"salary_max":252000,"location":"New York, NY","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["distributed-systems","payments","llm","agents","alignment"],"apply_url":"https://navan.com/careers/openings?gh_jid=8147410","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T12:55:34Z","expires_at":"2026-09-28T13:50:14.244228Z","created_at":"2026-08-29T13:50:14.443001Z","updated_at":"2026-08-29T13:50:14.443001Z","company_name":"Navan","company_slug":"navan","company_logo_url":"https://www.google.com/s2/favicons?domain=navan.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/1edaacf5-142d-4d7d-bca8-60df2de49655"},{"id":"1cab6a2a-2b5f-4e26-b0dd-0a2b833905b0","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Software Engineer, RL Data Platform","slug":"staff-software-engineer-rl-data-platform-224ae32b","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 RL Data Platform team builds the systems that produce, move, and serve the human data Claude learns from: the interfaces humans use to give feedback, the pipelines that turn raw feedback into training signal, and the tooling researchers use to launch, monitor, and inspect data collection. Every RL run depends on a steady supply of high-quality data - human feedback, expert demonstrations, graded transcripts - and when a researcher has an idea for new data on Monday, our job is to make it collectable by Wednesday and in the training mix by Friday.\n This is a full-stack, ownership-heavy role on a small, senior team. You'll design and ship web interfaces used by thousands of expert annotators, build the backend services and data pipelines behind them, and work directly with RL researchers to understand what data they need and why. You'll scope your own projects, make architectural calls, and see them through to production. We're looking for engineers who treat researchers as their users, build for reliability first, and care as much about the shape of the data leaving the system as the UI going into it.\n Key responsibilities \n \n \n Design, build, and operate the feedback and data collection interfaces used by human annotators, domain experts, and internal researchers.\n \n Build and maintain the backend services, APIs, and pipelines that route model samples to humans and return structured feedback to training.\n \n Own the reliability, latency, and usability of systems that run continuously against live model endpoints.\n \n Partner with RL researchers to translate loosely specified data needs into well-scoped collection campaigns and the tooling to run them.\n \n Build dashboards, monitoring, and inspection tools so researchers can see data quality and throughput without asking an engineer.\n \n Identify and remove the bottlenecks between \"we want this data\" and \"it's in the training mix\".\n \n Minimum qualifications \n \n \n Strong full-stack engineering skills, with production experience in TypeScript/React on the frontend and Python on the backend.\n \n Experience designing and operating backend services and data pipelines that other teams depend on.\n \n A track record of owning projects end-to-end, from an ambiguous brief to something in production that people use.\n \n Comfort working directly with technical stakeholders whose needs change week to week, and the judgment to push back when something isn't worth building.\n \n Effective use of AI tools in your own day-to-day work.\n \n Care about the societal impacts of your work.\n \n Preferred qualifications \n \n \n Experience building annotation, labelling, evaluation, or other human-in-the-loop data tooling.\n \n Experience with RLHF, preference data, or other human-feedback pipelines for ML systems.\n \n Experience shipping researcher-facing or other expert-facing internal tools people love: interviewing users, hunting down friction, measurably improving the experience.\n \n Experience running experiments on data collection interfaces and using the results to improve data quality.\n \n Experience working with crowdworker or expert vendor platforms at scale.\n \n Familiarity with how LLMs are trained and evaluated.\n \n Representative projects \n \n \n Build an interface that lets a domain expert review a long agentic transcript, flag the step where things went wrong, and write a corrected continuation - with the result landing in a training-ready format.\n \n Rework the sampling path between our feedback interfaces and model endpoints to cut time-to-first-sample for annotators.\n \n Build a campaign launcher that lets a researcher stand up a new data collection effort (task, rubric, population, quality checks) without writing code.\n \n Instrument annotator behaviour to detect low-effort or adversarial work and surface it to the quality team automatically.\n \n Design the data model for a kind of feedback we haven't collected before, and ship the pipeline that gets it into the training mix.\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $320,000 — $405,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job","salary_min":320000,"salary_max":405000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["data-pipeline","llm","reinforcement-learning","agents","alignment","research"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5404730008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-27T13:21:33Z","expires_at":"2026-09-28T13:30:43.093536Z","created_at":"2026-08-27T13:30:43.573151Z","updated_at":"2026-08-29T13:30:43.242369Z","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/1cab6a2a-2b5f-4e26-b0dd-0a2b833905b0"},{"id":"d9e245d1-a6c7-4071-9742-6a6ed60d8557","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Research Engineer, RL Data Platform","slug":"staff-research-engineer-rl-data-platform-41e9b926","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 RL Data Platform team builds the systems that produce, move, and serve the human data Claude learns from: the interfaces humans use to give feedback, the pipelines that turn raw feedback into training signal, and the tooling researchers use to launch, monitor, and inspect data collection. Every RL run depends on a steady supply of high-quality data - human feedback, expert demonstrations, graded transcripts - and when a researcher has an idea for new data on Monday, our job is to make it collectable by Wednesday and in the training mix by Friday.\n This is a full-stack, ownership-heavy role on a small, senior team. You'll design and ship web interfaces used by thousands of expert annotators, build the backend services and data pipelines behind them, and work directly with RL researchers to understand what data they need and why. You'll scope your own projects, make architectural calls, and see them through to production. We're looking for engineers who treat researchers as their users, build for reliability first, and care as much about the shape of the data leaving the system as the UI going into it.\n Key responsibilities \n \n \n Design, build, and operate the feedback and data collection interfaces used by human annotators, domain experts, and internal researchers.\n \n Build and maintain the backend services, APIs, and pipelines that route model samples to humans and return structured feedback to training.\n \n Own the reliability, latency, and usability of systems that run continuously against live model endpoints.\n \n Partner with RL researchers to translate loosely specified data needs into well-scoped collection campaigns and the tooling to run them.\n \n Build dashboards, monitoring, and inspection tools so researchers can see data quality and throughput without asking an engineer.\n \n Identify and remove the bottlenecks between \"we want this data\" and \"it's in the training mix\".\n \n Minimum qualifications \n \n \n Strong full-stack engineering skills, with production experience in TypeScript/React on the frontend and Python on the backend.\n \n Experience designing and operating backend services and data pipelines that other teams depend on.\n \n A track record of owning projects end-to-end, from an ambiguous brief to something in production that people use.\n \n Comfort working directly with technical stakeholders whose needs change week to week, and the judgment to push back when something isn't worth building.\n \n Effective use of AI tools in your own day-to-day work.\n \n Care about the societal impacts of your work.\n \n Preferred qualifications \n \n \n Experience building annotation, labelling, evaluation, or other human-in-the-loop data tooling.\n \n Experience with RLHF, preference data, or other human-feedback pipelines for ML systems.\n \n Experience shipping researcher-facing or other expert-facing internal tools people love: interviewing users, hunting down friction, measurably improving the experience.\n \n Experience running experiments on data collection interfaces and using the results to improve data quality.\n \n Experience working with crowdworker or expert vendor platforms at scale.\n \n Familiarity with how LLMs are trained and evaluated.\n \n Representative projects \n \n \n Build an interface that lets a domain expert review a long agentic transcript, flag the step where things went wrong, and write a corrected continuation - with the result landing in a training-ready format.\n \n Rework the sampling path between our feedback interfaces and model endpoints to cut time-to-first-sample for annotators.\n \n Build a campaign launcher that lets a researcher stand up a new data collection effort (task, rubric, population, quality checks) without writing code.\n \n Instrument annotator behaviour to detect low-effort or adversarial work and surface it to the quality team automatically.\n \n Design the data model for a kind of feedback we haven't collected before, and ship the pipeline that gets it into the training mix.\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $500,000 — $850,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job","salary_min":500000,"salary_max":850000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","reinforcement-learning","alignment","data-pipeline","search","agents","research"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5404725008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-27T13:04:41Z","expires_at":"2026-09-28T13:30:37.077517Z","created_at":"2026-08-27T13:30:36.814345Z","updated_at":"2026-08-29T13:30:37.227889Z","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/d9e245d1-a6c7-4071-9742-6a6ed60d8557"},{"id":"253c13f4-0eef-4662-ba68-c99e77924251","company_id":"adc4981a-d4ff-4939-952f-362f51e1291d","title":"Sr. Manager, Security Engineering","slug":"sr-manager-security-engineering-e11dfd0b","description":"Our Mission: \n 6sense's mission is to multiply what matters: growth, retention, and efficiency.  We envision a future where companies, teams and people reach their full potential.\n Our People: \n People are the heart and soul of 6sense. We serve with passion and purpose. We live by our Being 6sense values of Win as One Team, Stay Curious, Do The Right Thing, Own the Outcome, and Create Belonging.  Every 6sensor plays a part in defining the future of our industry-leading technology.  6sense is a place where difference-makers roll up their sleeves, take risks, act with integrity, and measure success by the value we create for our customers.  We want 6sense to be the best chapter of your career. \n \n Senior Manager, Security Engineering\n Business Technology, Security \n REPORTING AREA\n Security - CISO\n FUNCTION\n Business Technology\n TEAM MODEL\n United States and India\n LEADERSHIP SCOPE\n Application/Product Security; Infrastructure/Cloud Security; Vulnerability Management\n ROLE TYPE\n Leader with technical depth\n ENVIRONMENT\n AI-first, cloud-native SaaS\n Role Purpose\n Lead the security engineering organization that protects 6sense's AI-enabled, cloud-native SaaS platform. This leader owns Vulnerability Operations, Infrastructure Security, and Application/Product Security, and is accountable for building scalable security capabilities that enable rapid product delivery without compromising customer trust, resilience, or compliance. The role leads a distributed team across the United States and India and combines strategic leadership with credible technical judgment.\n Leadership Mandate\n \n Build one integrated security engineering operating model across the three teams, with clear ownership, service expectations, priorities, and measurable outcomes.\n Partner with Product, Engineering, Cloud Infrastructure, Data, AI/ML, Security Operations, Privacy, GRC, and Enterprise Technology leaders to embed security into planning and delivery.\n Create an inclusive, high-accountability culture across time zones using clear decisions, durable documentation, effective handoffs, and intentional overlap for critical work.\n Balance hands-on technical engagement with people leadership, program ownership, stakeholder influence, and executive-level risk communication.\n \n Core Responsibilities\n 1. Organization and People Leadership\n \n Lead, coach, and develop managers and engineers across the United States and India. Establish role clarity, career paths, succession coverage, and consistent performance expectations.\n Create an operating cadence that supports asynchronous execution, reliable cross-region handoffs, rapid escalation, and shared accountability.\n Build workforce and capacity plans aligned to product growth, AI investment, risk, and business priorities.\n Foster a culture of constructive challenge, disagree and commit, continuous learning, quality, and automation-first improvement.\n \n 2. AI and Product Security\n \n Own the security strategy for AI-enabled product capabilities from design through production, including threat modeling, architecture review, secure development standards, testing, monitoring, and release readiness.\n Address AI-specific risks such as prompt injection, insecure tool or agent access, sensitive-data exposure, model and data pipeline integrity, excessive agency, abuse, and third-party model or service dependencies.\n Partner with AI/ML, Product, and Engineering teams to define secure patterns for models, agents, retrieval-augmented generation, application programming interfaces, data access, and human approval controls.\n Advance product security practices including secure software development lifecycle controls, code and design review, application security testing, penetration testing, security champions, and coordinated vulnerability disclosure or bug bounty.\n \n 3. Vulnerability Operations\n \n Own end-to-end vulnerability discovery, prioritization, remediation governance, exception management, and validation across applications, cloud infrastructure, containers, endpoints, operating systems, and third-party components.\n Move beyond severity-only prioritization by incorporating exploitability, internet exposure, asset criticality, data sensitivity, available compensating controls, and active threat intelligence.\n Improve remediation speed and predictability through automation, clear service-level objectives, transparent ownership, and decision-ready reporting.\n Establish effective coverage for software supply chain risk, including open-source dependencies, build systems, artifacts, secrets, and continuous integration and delivery pipelines.\n \n 4. Infrastructure and Cloud Security\n \n Own preventive and detective security guardrails for the AWS environment, infrastructure as code, containers, identity and access, network boundaries, workloads, secrets, logging, and data services.\n Partner with Infrastructure and Platform Engineering to make secure cloud patterns easy to adopt and to reduce reliance on man","salary_min":204721,"salary_max":254258,"location":"New York, NY","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["rag","security","agents","data-pipeline","alignment","llm","cloud"],"apply_url":"https://boards.greenhouse.io/6sense/jobs/8139157?gh_jid=8139157","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-26T13:37:13Z","expires_at":"2026-09-28T13:41:52.041844Z","created_at":"2026-08-26T13:41:05.372167Z","updated_at":"2026-08-29T13:41:52.194748Z","company_name":"6sense","company_slug":"6sense","company_logo_url":"https://www.google.com/s2/favicons?domain=6sense.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/253c13f4-0eef-4662-ba68-c99e77924251"},{"id":"fef86a6f-88bb-4446-95f7-e78d16d7e82d","company_id":"a0000000-0000-0000-0000-000000000001","title":"Applied AI Engineer, Beneficial Deployments (Life Sciences)","slug":"applied-ai-engineer-beneficial-deployments-life-sciences-59ac98a0","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 Beneficial Deployments Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits, foundations, and mission-driven organizations to deploy Claude in education, global health, economic mobility, and life sciences — focusing on raising the floor for those who need it most.\n About the Role We're looking for an Applied AI Engineer to join our Beneficial Deployments team, focused on maximizing the impact of Claude in the life sciences. Our goal is ambitious: accelerate scientific progress from R\u0026D through translation by an order of magnitude. That means making Claude the go-to tool for the life sciences ecosystem from early discovery in academia to paradigm shifting biotech to reimaging pharma pipelines  — and building the technical infrastructure to back that up.\n You'll work directly with flagship research partners like The Howard Hughes Medical Institute (HHMI) and The Allen Institute, embedded in their scientific workflows. This isn't consulting from the outside — you'll be building alongside their engineers, prototyping agents that fit into real research pipelines, and developing the ecosystem-level tooling (MCP servers, benchmarks, reusable agent skills) that extends Claude's usefulness across the broader life sciences community. This role will be part of the founding Beneficial Deployments Applied AI team focused on bringing life sciences closer to the frontier.\n Responsibilities \n \n Partner deeply with flagship life sciences research institutions — understand their scientific workflows end-to-end, build hands-on with their engineering teams, and help take projects from early exploration to production systems integrated into how they do science day-to-day.\n Develop reusable ecosystem infrastructure, like MCP servers for domain-specific data sources (genomics platforms, literature databases, experimental repositories), instruments, scientifically-grounded benchmarks, and agent skills that other institutions can adopt without starting from scratch.\n Identify what's actually hard about deploying AI in life sciences (heterogeneous data, auditability requirements, the prototype-to-trust gap) and feed those findings back to product, engineering, and research.\n Create technical content and documentation that lets partners self-serve, so what works for one institution can scale globally without the same level of hand-holding.\n \n You Might Be a Good Fit If You Have: \n \n Deep research experience in life sciences, biomedical research, or scientific computing. Bonus if you've studied genomics, neuroscience, or drug discovery specifically and are comfortable getting deeply technical with academics.\n Experience building LLM-powered tools or applications: prompting, context engineering, agent architectures, evaluation frameworks.\n Builder credibility from shipping production code as a software engineer, forward-deployed engineer, or technical founder.\n A scrappy mentality–comfortable wearing multiple hats, building from scratch, driving clarity in ambiguous situations, and doing whatever it takes to further the mission.\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 $280,000 — $320,000 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 yourse","salary_min":280000,"salary_max":320000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["healthcare","fine-tuning","alignment","llm"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5021015008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-24T22:31:29Z","expires_at":"2026-09-28T13:30:14.253248Z","created_at":"2026-08-25T18:26:11.30816Z","updated_at":"2026-08-29T13:30:14.406712Z","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/fef86a6f-88bb-4446-95f7-e78d16d7e82d"},{"id":"22350dcd-2163-4b68-95ae-b6b30ca73990","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff + Sr. Software Engineer, Scaling","slug":"staff-sr-software-engineer-scaling-cf5b270f","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 Our Inference team is responsible for building and scaling the critical systems that serve Claude to millions of users worldwide. We bring Claude to life by serving our models via the industry’s largest compute-agnostic inference deployments. We are responsible for the entire stack from intelligent request routing to fleet-wide orchestration across diverse AI accelerators.\n The team has a dual mandate: maximizing compute efficiency to reliably serve our explosive customer growth, while enabling breakthrough research by giving our scientists the high-performance inference infrastructure they need to develop next-generation models. We tackle complex, distributed systems challenges across multiple accelerator families and emerging AI hardware running in multiple cloud platforms.\n Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size \u0026 span of the inference fleet requires sophisticated routing, scaling, and networking systems.\n Key responsibilities\n \n Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide\n Develop resilient, flexible systems that adapt in real time to real world events\n Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators and multiple cloud providers\n Maximize compute efficiency and optimize cost across the fleet by autoscaling and orchestrating production, research, and experimental workloads across multiple cloud providers\n Build and operate production-grade deployment pipelines for releasing new models to users\n Provide high-performance inference infrastructure that enables researchers to develop next-generation models\n Integrate new AI accelerator platforms and support inference for new model architectures\n \n Minimum qualifications\n \n Significant software engineering experience, particularly with distributed systems\n Results-oriented, with a bias towards flexibility and impact\n Willingness to pick up slack, even if it goes outside your job description\n Desire to learn more about machine learning systems and infrastructure\n Thrive in environments where technical excellence directly drives both business results and research breakthroughs\n Care about the societal impacts of your work\n \n Preferred qualifications\n \n Experience with high-performance, large-scale distributed systems\n Experience implementing and deploying machine learning systems at scale\n Experience with load balancing, request routing, or traffic management systems\n Familiarity with LLM inference optimization, batching, and caching strategies\n Experience with Kubernetes and cloud infrastructure (AWS, GCP, Azure)\n Proficiency in Python or Rust\n \n Representative projects\n \n Designing intelligent routing algorithms that optimize request distribution across many accelerators in different environments\n Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads\n Building production-grade deployment pipelines for releasing new models to millions of users reliably\n Contributing to new inference features\n Supporting inference for new model architectures\n Analyzing observability data to tune performance based on real-world production workloads\n Managing multi-region deployments and geographic routing for global customers\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 qua","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","llm","distributed-systems","cloud","infrastructure"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5400012008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-24T19:24:05Z","expires_at":"2026-09-28T13:30:44.153072Z","created_at":"2026-08-25T18:26:22.790216Z","updated_at":"2026-08-29T13:30:44.302734Z","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/22350dcd-2163-4b68-95ae-b6b30ca73990"},{"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":["llm","robotics","alignment","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":"2026-09-28T13:30:26.153428Z","created_at":"2026-08-25T18:26:14.591016Z","updated_at":"2026-08-29T13:30:26.304799Z","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":"28b05347-ce05-4abb-9151-3f23b80ec6ec","company_id":"a0000000-0000-0000-0000-000000000001","title":"Manager Applied AI Architecture, Financial Services","slug":"manager-applied-ai-architecture-financial-services-c4ba41fa","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 manager of the Financial Services Solutions Architect team within Applied AI at Anthropic, you will drive the adoption of frontier AI in partnership with the rest of the go to market organization. We work with customers that include companies across banking, insurance, asset management, and payment providers. You will be responsible for leading and growing the pre-sales team that partners with account executives to help those companies understand and deploy Anthropic’s products, including Claude Code, Cowork, and the Claude Development Platform (our API). This will include leveraging your technical skills and consultative sales experience to hire great people, establish processes for the team to scale, and represent Anthropic directly at strategic customer engagements.\n Responsibilities:  \n \n Hire, manage, and guide a team of pre-sales Solutions Architects by providing both technical guidance and career development.\n Set goals for your team that establish baseline expectations for performance in collaboration with sales and other cross-functional teams.\n Act as a technical sponsor for high-value strategic customers and advise them on their overall AI adoption strategies or top use case scoping and deployment.\n Partner closely with sales leadership to identify new strategies to drive adoption of Anthropic products within specific verticals or horizontal use cases.\n Work with cross-functional teams like product and engineering to ensure Anthropic prioritizes customer feedback or resolves blockers to adoption.\n Travel to customer sites or conferences for executive-level sessions, technical workshops, and relationship building.\n Establish a shared vision for creating solutions that enable beneficial and safe AI in technology products.\n Contribute to thought leadership through conference presentations, webinars, and technical content creation.\n Stay current with emerging AI trends and the evolving ecosystem.\n \n You may be a good fit if you :\n \n 7+ years of experience as a Solutions Architect, Sales Engineer, or similar pre-sales technical role.\n 3+ years of technical pre-sales management experience.\n Have sold complex technical products to Financial Services companies.\n Have deep technical proficiency with enterprise AI use cases and API integrations or enterprise solution rollouts.\n Understand how to contribute to running a GTM organization anchored on a consumption business model, not SaaS sales cycles.\n Thrive in building and rapidly scaling teams and processes within ambiguous and fast-moving environments.\n Have excellent communication, collaboration, and coaching abilities.\n Strong executive presence and ability to foster deep relationships with technical leaders and engineering teams.\n Have at least a high level familiarity with the architecture and operation of LLMs.\n Have a passion for making powerful technology safe and societally beneficial.\n Stay up-to-date and informed by taking an active interest in emerging research and industry trends within AI.\n \n Strong candidates may have :\n \n Enterprise pre-sales leadership at scale : 5+ years leading solution architect teams through hypergrowth (ideally 10 to 50+ people), with direct experience managing senior individual contributors and developing junior talent in complex enterprise software sales environments.\n AI Technical Depth + Executive Engagement : Hands-on experience with AI platforms and enterprise integration patterns, combined with proven track record engaging C-level stakeholders in $10M+ technical evaluations and enterprise sales cycles.\n Deep FSI GTM Experience : Demonstrated success adapting technical approaches to customers in banking, insurance, payment providers, or asset management.\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 $315,000 — $380,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas!","salary_min":315000,"salary_max":380000,"location":"New York, NY","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["alignment","payments","llm","fintech"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5390894008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-21T01:55:46Z","expires_at":"2026-09-28T13:30:23.765948Z","created_at":"2026-08-25T18:26:13.960891Z","updated_at":"2026-08-29T13:30:23.916624Z","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/28b05347-ce05-4abb-9151-3f23b80ec6ec"},{"id":"159bc0f7-eda7-4229-ad58-4c05b7326801","company_id":"a0000000-0000-0000-0000-000000000001","title":"Security Engineer, Corporate Security","slug":"security-engineer-corporate-security-1f5d1dca","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 Corporate Security protects the environment Anthropic's people work in every day: their laptops and phones, their identities, the tools they collaborate in and the company data that flows through all of it. Everything that makes Claude what it is sits behind that environment. We keep company access on devices we manage, make those devices hard to compromise and right-size what any one of them can reach, while caring a great deal about the day-to-day experience of the people using them. The company is growing quickly and this team is growing with it, so we treat the work as an engineering discipline: controls as code and automation over queues, built to scale with headcount rather than strain against it.\n As a Security Engineer here you'll drive significant parts of that work end to end. You'll set technical direction and turn it into shipped tooling. When a control collides with someone's workflow, you'll find the path that keeps them moving without giving up the protection. You'll be handed problems rather than task lists and you'll find as many yourself: threat-modeling the environment to surface what matters, fixing it and bringing the evidence that shapes what the team prioritizes next. This is a senior, hands-on individual contributor role.\n Key responsibilities \n \n Drive endpoint hardening across macOS, Windows, Linux, and ChromeOS, including device management configuration, application allowlisting, patching, and browser policy, favoring controls that are versioned, reviewable, and repeatable over one-off configuration\n Extend device-trust and zero-trust access controls so company systems are reached from managed devices bound to the right person and carrying the right level of access, treating the experience of fellow employees as a design constraint rather than an afterthought\n Build the automation and integrations that let the team scale with the company: joiner/mover/leaver automation across identity and device management, exception and expiry workflows, posture-driven policy, and Claude-assisted triage of review queues\n Lead SaaS and identity governance, including third-party OAuth grants, delegated admin access, chat-platform apps, browser extensions, and software security reviews, turning recurring decisions into policy and tooling\n Partner across the wider Security team, IT, and Engineering on telemetry, detections, and shared standards, and help define how a company that increasingly runs on AI agents does so securely and at scale\n \n Minimum qualifications \n \n Hands-on endpoint security engineering on macOS, Windows, Linux, or ChromeOS, such as MDM and declarative device management profile engineering, application allowlisting or binary authorization, system extensions and endpoint security frameworks, or their platform equivalents\n Proficiency in Python and scripting languages generally; you architect and build integrations, automation, and internal tooling as a normal part of the job, and can write a detection when the work calls for it\n Working depth in identity and access management, SaaS security, and zero-trust access\n Threat-modeling judgment that finds the problems worth solving and the ability to scope them, define \"done,\" and drive them to completion\n Care for Anthropic's mission and the part corporate security plays in it\n \n Preferred qualifications \n \n Experience defining the scope and choosing the tooling for a security program rather than inheriting it\n Experience shipping an enforcement change to a large user population: using data to find what will break before it does, staging the rollout, building the alternative path for affected workflows, and moving people onto it ahead of enforcement\n Endpoint depth across more than one of macOS, Windows, Linux, and ChromeOS, with the judgment to harden for the threats that matter rather than to a checklist\n Mobile security across managed and BYOD contexts, including protecting people and devices in higher-risk settings such as international travel\n Experience bringing security governance to a modern SaaS environment, including third-party integrations, delegated access, and the long tail of internally built and AI-generated apps, in a way that speeds decisions up rather than slowing them down\n Configuration-as-code, infrastructure-as-code, and CI/CD applied to corporate infrastructure\n LLM-assisted security tooling you built that materially changed what a team could cover, and the judgment to know which work to hand to a model, which to keep, and how to combine the two\n A track record of getting security controls adopted across an organization through influence and partnership rathe","salary_min":320000,"salary_max":405000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["agents","security","alignment","llm"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5397319008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-21T00:41:05Z","expires_at":"2026-09-28T13:30:34.344517Z","created_at":"2026-08-25T18:26:18.183489Z","updated_at":"2026-08-29T13:30:34.49725Z","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/159bc0f7-eda7-4229-ad58-4c05b7326801"},{"id":"f870f515-f436-4a0b-b447-09b7e3201f15","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Software Engineer, Claude Managed Agents","slug":"staff-software-engineer-claude-managed-agents-8e1781b3","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 experienced backend and distributed systems engineers to join the Agentic Systems team within our Platform organization. Agentic Systems builds Claude Managed Agents: the hosted platform for building, running, and scaling production agents on Claude. Instead of every developer hand-rolling an agent loop, sandboxed execution, state management, credential handling, and error recovery — and reworking all of it with every model release — Managed Agents pairs an Anthropic-built agent harness with production infrastructure for sessions, environments, tools, memory, and permissions, exposed through a small set of composable APIs designed to stay stable as models and harnesses evolve. It powers agentic products inside Anthropic as well as those built by customers on the Claude Platform.\n Managed Agents is in public beta and growing quickly, and this is still an early team with a lot of surface area left to define. You'll drive 0 → 1 efforts from ideation through GA, own systems end to end from API design through operations, and partner closely with product, research, developer experience, and go-to-market teams to figure out what \"managed\" should mean for the next generation of agents. You should be comfortable going deep on hard distributed systems problems, care about APIs as a product in their own right, and be motivated by turning ambiguous ideas into high-quality, shipped platform capabilities that other engineers build their products on.\n What you'll do\n Scale the platform. Managed Agents runs long-lived, stateful sessions that execute autonomously for minutes or hours/days, persist through disconnections, and resume cleanly — across Anthropic-hosted sandboxes, self-hosted environments on customer infrastructure, and other clouds. You'll design and operate the systems underneath that: durable session and event storage, sandbox orchestration, streaming, scheduling, and multi-tenant isolation. Reliability, latency, and cost efficiency are product features here, and you'll own them in production.\n Evolve the harness — and prove it with evals. The harness is the loop that calls Claude, routes tool calls, manages context (caching, compaction, memory), and recovers from errors. Harnesses encode assumptions about what the model can't yet do on its own, and those assumptions go stale as models improve. You'll work alongside research to revisit them with each model generation, build the eval infrastructure that measures harness quality against research baselines and real customer workloads, and hold the bar that lets us say our harness gets the most out of Claude.\n Help builders get the most out of Claude. Our customers — internal and external — are building agents both as products for their users and to transform their own operations. You'll ship the capabilities that raise the ceiling on what those agents can do: outcome-driven execution where developers specify success criteria and a budget and Claude iterates until it gets there, multi-agent orchestration, memory, and the observability and tracing that make long-running agents debuggable. The goal is the highest intelligence per dollar of any agent platform, delivered safely.\n Design APIs that outlast their implementations. Agents, environments, sessions, vaults, and event streams are interfaces thousands of developers build against and that our own products depend on. You'll shape those primitives — versioning, ergonomics across API, SDK, and CLI, sensible defaults, escape hatches — with the expectation that the implementations underneath will change many times while the contracts hold.\n You might be a good fit if you:\n \n Have a minimum of 8 years of practical experience as a backend, distributed systems, or infrastructure engineer\n Have built and operated stateful, long-running, or high-throughput systems in production — workflow orchestration, streaming, storage, container or job orchestration — and can reason rigorously about durability, consistency, failure modes, and cost\n Have strong product sense and treat API design as a craft; you care about the developer on the other side of the interface and can ideate and execute product strategy with cross-functional partners in new domains\n Are excited by 0 → 1 work and comfortable navigating ambiguity, and have ideally operated in both early-stage and more mature team or company settings\n Use Claude or other AI tools as a core part of how you build software, and have opinions about what makes an agent harness good\n Take full ownership of your work — from design through build, deployment, and operations (including on-ca","salary_min":405000,"salary_max":485000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","api-design","distributed-systems","mlops","alignment","agents"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5395767008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-20T15:55:19Z","expires_at":"2026-09-28T13:30:39.03655Z","created_at":"2026-08-25T18:26:20.027221Z","updated_at":"2026-08-29T13:30:39.187556Z","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/f870f515-f436-4a0b-b447-09b7e3201f15"},{"id":"6eaba005-4853-4501-b7ff-591fb3da2217","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Software Engineer, Product Sandboxing","slug":"staff-software-engineer-product-sandboxing-3cae3b3c","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 build and run the secure execution environment behind Claude's agentic capabilities. When Claude writes and runs code, browses the web, or uses a computer, that happens on infrastructure our team owns. We work at the intersection of systems engineering and security. The goal is to make untrusted code execution safe, fast, and reliable enough that product teams don't have to think about it. This is the layer between the model and the outside world, and it has to hold up at scale for every Anthropic product. We're hiring engineers who have experience building for containerized workloads and have a keen eye for building products used by millions of customers.\n What you'll do\n You'll independently scope complex, multi-month projects, drive cross-org alignment through ambiguous problem spaces, and make architectural decisions that shape how Anthropic builds and scales its products. You'll partner directly with research to productize cutting-edge capabilities, and will have lasting impact on the platform that hundreds of thousands of companies and internal/external engineers depend on every day.\n You might be a good fit if you:\n \n Have a minimum of 8 years of practical experience as a backend or platform engineer building scalable distributed systems, ideally operating at tech lead level or equivalent distributed systems, cloud-native products, developer tools, or external developer facing products\n Have strong fundamentals in service-oriented architectures, networking, and systems design, ideally having owned both the technical vision and execution of a foundational platform system end to end \n Are proficient in Python, Go, Rust, or similar systems languages\n Have experience with cloud infrastructure (GCP, AWS, or Azure), container orchestration (Kubernetes), and/or multi-cloud networking \n Take full ownership of your work—from design through deployment and operations\n Can navigate ambiguity and make sound technical decisions independently, and have ideally operated in 0 to 1 and more mature team or company settings \n Take a product-focused approach to platform work and care about building solutions that are robust, scalable, and easy to us\n \n Deadline to apply:  None. Applications will be reviewed on a rolling basis. \n Location Preference: Preference will be given to candidates based in NY, SEA, SF or the Bay Area given the current location of team. \n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $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, 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","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","distributed-systems","agents","cloud"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5394943008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-19T00:59:49Z","expires_at":"2026-09-28T13:30:42.889934Z","created_at":"2026-08-25T18:26:22.02817Z","updated_at":"2026-08-29T13:30:43.046513Z","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/6eaba005-4853-4501-b7ff-591fb3da2217"},{"id":"c14bafd3-c9dc-471a-861f-4f1abb2404c8","company_id":"a0000000-0000-0000-0000-000000000001","title":"Finance Systems Engineer, Finance and Strategy","slug":"finance-systems-engineer-finance-and-strategy-ca9c30eb","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the Role \n We are looking for a Finance \u0026 Strategy (FP\u0026A)  Systems Engineer to join our Finance Systems team at Anthropic. In this role, you will be responsible for building and maintaining platforms that support our core Financial Planning, Forecasting and Analytics processes. You will bring deep hands-on expertise in EPM platforms like Anaplan, Pigment and data platforms like BigQuery, who writes integrations, tooling, and production code that connect them to Anthropic’s ERP and data warehouse systems. You'll work closely with Corporate Finance \u0026 strategy stakeholders to translate business requirements into innovative technical solutions, maintain data integrity, and drive continuous improvements to our financial systems infrastructure.\n You'll manage day-to-day Finance system operations, support critical financial processes and monthly Forecasting cycles, and take on more ambitious system projects over time, including using Claude to automate FP\u0026A work, help build scalable solutions that enable efficient financial planning, forecasting, and reporting as we continue to grow.\n Responsibilities \n Systems Administration and Support \n \n \n Serve as a primary system administrator for our financial planning platform (Pigment), maintaining system health and optimal performance\n \n Manage Finance applications, data, user access \u0026 security,  system configurations, version management to ensure appropriate controls and governance.\n \n Provide technical support and troubleshooting for end-users, resolving issues and answering system-related questions\n \n System Development and Enhancement  \n \n \n Design, build, and maintain applications, Financial  models and workflows with in-house tools and EPM platform like Pigment to support financial planning, budgeting, forecasting, and reporting processes\n \n Develop and maintain secure dataflows, integrations using Rest APIs to connect FP\u0026A platforms, data warehouse with enterprise systems (e.g., Workday Financials, Salesforce CRM, etc.)\n \n Develop SQL-based data models, ETL pipelines, and reporting infrastructure to support financial close, forecasting, and business intelligence. \n \n Business Partnership and Process Improvement \n \n \n Partner with Finance \u0026 Strategy (FP\u0026A), Accounting, and other Finance teams to understand business problems and use AI tools to build cutting edge solutions\n \n Support Monthly Forecast, Annual \u0026 Long Range planning, Workforce planning, OPEX Forecasting, Balance Sheet \u0026 Cash flow forecasting processes.\n \n Identify and implement process and Finance platform  improvements. \n \n Participate in testing and validation of system changes, ensuring accuracy and reliability\n \n Assist with training and onboarding of new system users\n \n Data Management and Quality \n \n \n Ensure the accuracy and integrity of financial data across systems\n \n Develop and maintain data validation rules and quality checks\n \n Troubleshoot data discrepancies and work with relevant teams to resolve issues\n \n Support data migration and transformation activities as needed\n \n Minium Qualifications \n \n \n Have 8+ years of experience in FP\u0026A systems -  EPM platforms, Finance data warehouse, with a focus on financial planning, forecasting and analysis.\n \n Have hands-on experience administering and developing solutions in enterprise planning platforms (e.g., Pigment, Anaplan, Adaptive Planning, or similar EPM tools)\n \n Possess strong engineering and technical skills including advanced SQL and data modeling skills, creating and maintaining system integrations and data pipelines.\n \n Have demonstrated ability to translate business requirements into technical specifications and system designs.\n \n Have a strong understanding of FP\u0026A processes, financial reporting, and accounting principles\n \n Preferred Qualifications \n \n \n Techno-functional: you're someone who is a CFA but also a hands on developer.\n \n Experience owning changes inside a shared production codebase alongside a product engineering team\n \n Warehouse and analytics-engineering skills such as dbt, BigQuery, or comparable\n \n Experience building robust Finance applications with LLMs \n \n Knowledge of programming or scripting languages (Python, JavaScript, etc.)\n \n Experience with Financial planning \u0026 analysis (CFA), experience with pre-IPO companies, supporting rapid growth and scaling financial systems accordingly.\n \n Understanding of financial data security and compliance requirements\n \n Certification in relevant planning platforms (e.g., Pigment, Anaplan Model Builder)\n \n Project management skills and experience leading system implementation workstreams\n The annual compensation range for t","salary_min":205000,"salary_max":270000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","alignment","data-pipeline","api-design"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5390728008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-14T19:29:18Z","expires_at":"2026-09-28T13:30:20.439857Z","created_at":"2026-08-25T18:26:13.387151Z","updated_at":"2026-08-29T13:30:20.592133Z","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/c14bafd3-c9dc-471a-861f-4f1abb2404c8"},{"id":"7b9b8809-f3ac-4c1b-9808-82ec279c5fb4","company_id":"a0000000-0000-0000-0000-000000000001","title":"Software Engineer, Infrastructure, Interpretability","slug":"software-engineer-infrastructure-interpretability-3cb5ab0f","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 When you see what modern language models are capable of, do you wonder, \"How do these things work? How can we trust them?\"\n The Interpretability team at Anthropic works to understand what's actually happening inside trained models - and applies our best techniques to keep frontier AI safe as it rapidly improves.\n Think of us as doing \"neuroscience\" of neural networks using \"microscopes\" we build - or reverse-engineering neural networks like binary programs.\n More resources to learn about our work: \n \n \n Our Research blog - covering advances including Monosemantic Features and Circuits \n \n An Intro to Interpretability from our research lead, Chris Olah \n \n The Urgency of Interpretability from CEO Dario Amodei\n \n Engineering Challenges Scaling Interpretability - directly relevant to this role\n \n 60 Minutes segment - see a demo of tooling our team built\n \n New Yorker article - what it's like to work on one of AI's hardest open problems\n \n This role is an early hire on a new infrastructure effort within Interpretability: you'll help define its charter, not just execute it. \n Interpretability research requires deep access to frontier models while retaining a high degree of research flexibility. Your job is to build the paved path that makes that access secure by default, private by design, and low-friction for every researcher. The work spans four areas:\n \n \n Security : design the secure-by-default environments and access patterns that enable deep model access for an organization whose research requires it - done well, the same design improves both our security posture and research productivity.\n \n Privacy : build data-access patterns that ensure policy adherence as our research moves from theory into practical application\n \n Data \u0026 Compute Management : manage research data at petabyte scale and make efficient use of large accelerator fleets - storage lifecycle, capacity planning, and scheduling.\n \n Developer experience : agentic engineering, tooling and observability that keep researchers moving fast\n \n In this role, you’ll be deeply embedded alongside Interp Researchers to understand their workflows - building your understanding of the research as you go; at the same time you’ll bridge communication with Anthropic’s wider platform and security teams.. Every hour of researcher friction you remove is multiplied across the whole organization, and the infrastructure you build sets the pace at which interpretability results reach real safety decisions.\n Responsibilities:\n \n \n Design, build, and own shared infrastructure for Interpretability - research environments, data systems, and compute tooling that researchers rely on daily\n \n Lead cross-team efforts with our agentic engineering , security, compute, and storage platform teams, so that company-wide solutions serve research needs\n \n Discover and resolve major organization-wide developer experience issues\n \n Help take interpretability methods from research code to dependable audit pipelines\n \n You may be a good fit if you:\n \n \n Are highly proficient in at least one programming language (e.g., Python, Rust, Go, Java) and productive with Python\n \n Have significant experience building and operating secure and scalable software infrastructure - cloud systems, distributed systems, or developer tooling\n \n Have strong cross-functional communication skills - equally at home working with researchers and with platform and security teams\n \n Are extremely curious about unfamiliar domains\n \n Have a strong ability to prioritize the most impactful work and are comfortable operating with ambiguity and questioning assumptions\n \n Are curious about interpretability research and its role in AI safety (though no research experience is required!)\n \n Care about the societal impacts and ethics of your work\n \n Strong candidates may also have:\n \n \n Experience with cloud infrastructure (e.g. GCP or AWS), Kubernetes, networking and infrastructure-as-code\n \n Security engineering experience: identity / auth / access management, sandboxing, red teaming\n \n Experience with data warehousing, large-scale storage systems, and data lifecycle management - especially for research\n \n Experience with compute schedulers and accelerator fleet management\n \n Experience building developer productivity tooling and observability stacks\n \n Experience building tooling to accelerate research teams\n \n Representative Projects:\n \n \n Design and stand up a hardened research environment where researchers experiment directly on frontier model weights\n \n Build lifecycle management for petabytes of research data - visibility, retention, and cost efficiency\n \n B","salary_min":320000,"salary_max":485000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["distributed-systems","alignment","security","deep-learning","agents","cloud","research","infrastructure"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5388612008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-12T22:29:15Z","expires_at":"2026-09-28T13:30:35.838041Z","created_at":"2026-08-25T18:26:19.069491Z","updated_at":"2026-08-29T13:30:35.993171Z","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/7b9b8809-f3ac-4c1b-9808-82ec279c5fb4"},{"id":"35632b3a-4ec3-40c1-b519-5f7a4923469e","company_id":"a0000000-0000-0000-0000-000000000001","title":"Product Manager, New Markets and Monetization","slug":"product-manager-new-markets-and-monetization-ca933391","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 New Markets and Monetization team exists to bring transformational AI to every business. Model capabilities are compounding, and the Claude Platform is how businesses build with our models. Our job within the Claude Platform is to make sure that every industry, not just software, can build on frontier AI with our APIs and that everyone who builds on Claude prospers by it. \n The work falls into two pillars that reinforce each other. \n \n Verticals: identifying and building for the next API markets. \n Monetization: the commercial machinery that lets the platform do business anywhere, with anyone: a single way for usage that flows through partners, resellers, and other platforms.\n \n We're hiring the founding product managers onto this team, and this posting covers all of them. You will own one of the areas below outright, work day to day with a dedicated engineering lead and designer, and be measured on numbers that are company-level goals for the half. Almost none of this exists yet, so most weeks you will be the person defining the problem rather than receiving it.\n Key responsibilities \n \n Partner and platform billing. How usage that reaches Claude through a partner, reseller, or another platform is metered, attributed, and billed, and the program terms that go with it, so indirect volume can grow without our risk growing with it.\n Spend observability and controls. Giving enterprise buyers a precise view of what they spend and where, and turning that into limits and controls they can enforce, including programmatically.\n One account, and the startup path built on it. One login and one wallet across the API and Claude's subscriptions, so a builder's first commit, first production call, and first invoice are on a single plan.\n A vertical. The platform strategy for a particular industry: what builders there need that the platform doesn't yet do, which bets to make, and shipping them with the vertical's own product and go-to-market partners.\n \n Whatever your focus, you will:\n \n Build on primitives owned by the Billing Platform and Auth \u0026 Identity teams, and ship with Growth, Go-to-Market and Startups, Legal, Finance, and Data Science\n Structure the commercial terms yourself, whether that's pricing, revenue attribution, or partner and startup program terms, with Finance, Legal, and Business Development\n Talk to every side of the ecosystem, from enterprise buyers and startup builders to the partners that resell or embed Claude and the industry customers we're building for, and turn it into a roadmap where each new participant makes the platform more valuable to the rest\n Own the team's outcome metrics: the share of the platform's business outside coding, new startup revenue, volume unified across the API and Claude's subscriptions, and the volume partners book on Claude, and make sure the instrumentation exists to know whether what you shipped moved them\n Write the strategy, the specs, and the analysis yourself\n \n Minimum qualifications \n \n Have owned a developer platform, API, billing or money-movement product, or self-serve growth product end to end, and were the person accountable for its revenue or activation number (for most people this means five or more years as a PM, but we care about the ownership, not the years)\n Have built with or shipped on top of large language models, and have a view on what changes about billing, identity, or distribution when the customer is sometimes an agent\n Are technically fluent: you read API docs, work through a billing, identity, or attribution design with engineers, and make calls on platform primitives yourself\n Pull your own data: SQL or equivalent, to define a metric, build a funnel, or size a market\n Have negotiated pricing, revenue share, or program terms with Finance, Legal, or Business Development counterparts\n Write clearly enough that an engineer, an executive, and an external partner can each see the tradeoff you're making\n Care about Anthropic's mission, and specifically about growing this platform in a way where the people building on it share in the upside\n \n Preferred qualifications \n \n 8+ years of product management experience\n Worked on metering, usage attribution, reseller or cloud-marketplace channels, or enterprise spend management\n Taken a developer platform into a new industry, or built product in healthcare, life sciences, financial services, or another regulated industry\n Grown a developer product's self-serve or startup business, including its pricing and packaging\n Built account, identity, or subscription systems that span more than one product\n Taken a product from zero to one, wh","salary_min":305000,"salary_max":385000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["payments","alignment","healthcare","llm"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5386182008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-11T22:55:36Z","expires_at":"2026-09-28T13:30:27.535415Z","created_at":"2026-08-25T18:26:14.949015Z","updated_at":"2026-08-29T13:30:27.701466Z","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/35632b3a-4ec3-40c1-b519-5f7a4923469e"},{"id":"b622f8c2-d6ae-4c56-af48-a73a0563caa1","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Researcher, Cybersecurity Products","slug":"staff-researcher-cybersecurity-products-6eb1c07e","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 looking for a Capabilities Researcher to join the team building Claude Security. In this role, you'll identify which security capabilities in frontier models are ready to build on, measure how well they perform, and work out how to make them useful to customers who are not security experts.\n Frontier models have become substantially more capable at security work over recent generations, and they continue to improve with each release. That progress creates a set of practical questions: which capabilities are reliable enough to depend on, how they perform in realistic conditions, how they behave when an adversary is involved, and where their limits are. You'll be responsible for answering those questions through fast prototyping and rigorous evaluation, and your findings will shape what the team decides to build.\n You'll also work on making those capabilities usable. Together with engineers on the team, you'll design the scaffolding, tooling, and defaults that let a strong model capability do useful work for a non-expert, and you'll stay involved as it becomes a product.\n This is a research role on a product team, with a broad charge and real latitude in what you investigate. It suits someone who already has ideas about what AI should be able to do for security teams and wants the models, the time, and the engineering support to pursue them.\n Responsibilities \n \n Prototype rapidly to find define the AI frontier for cybersecurity work\n Design evaluations that measure model performance on the work security teams actually do\n Build the datasets, harnesses, and scoring those evaluations depend on\n Engage with the cybersecurity community to help define where AI can make the most impact\n Work with engineers and researchers to operationalize promising capabilities into something customers can rely on\n Track how model capabilities for security are changing, and what that means for what we build next\n Share findings that inform product direction, and partner with product leadership on priorities\n \n You may be a good fit if you: \n \n Have deep expertise in one or more security domains, such as vulnerability research, exploit development, reverse engineering, malware analysis, incident response, or offensive security\n Have built AI-powered tools or capabilities for security work\n Can get from an idea to a working prototype quickly, and abandon the ones that don't hold up\n Are comfortable designing rigorous evaluations and interpreting the results honestly\n Can write and communicate clearly about technical findings\n Have 7+ years of experience in security research, security engineering, or a closely related field\n \n Strong candidates may also have: \n \n Published research, CTF results, CVEs, or open source security tooling\n Experience with model evaluation, benchmarking, or red teaming\n Experience building agentic applications\n Familiarity with the safety considerations of AI in security contexts\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 $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. 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