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Location: Brazil Workplace: remote As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com   To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below represent the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.   OVERVIEW   We are looking for translators with experience in translating patents from English into Portuguese (Brazil)  (native-level fluency of Portuguese) with immediate availability for a patent translation project.   The ideal candidate will have strong experience in translating and proofreading patents, specifically in the field of Chemistry, Computer Science, Electricity.   Project Details:   Job Title: English to Portuguese (Brazil) Patent Linguist Start Date: ASAP Location: Remote Task Type: Translation, Copy Edit Content Type: Chemistry, Computer Science, Electricity Expected Weighted Volume Per Week: +5,000 words CAT Tool:  XTM Employment Type: Freelance Main Duties Translate patent-related content from English into Portuguese(Brazil) , with original meaning conveyed in a manner that is readable and understandable to target audience. Perform translation and copy edit from English (en-US) to Portuguese (pt-BR) for patent. Identify and correct linguistic errors, ensuring consistency in terminology, style, and adherence to client-specific guidelines. Provide detailed feedback to translators and create comprehensive quality reports. Ensure adherence to client-specific style guides, glossaries, and project guidelines. Utilize CAT tools (XTM) to review and assess translations efficiently. Manage weekly capacity to handle +5,000 words per locale and ensure timely task completion. Requirements BS/BA in linguistics, translation, biology, or related fields. 2+ years of work experience in translation, linguistic quality assessment, copywriting, or copy-editing, specifically in patents or technical content. Deep understanding of biological terminology and ability to adapt complex scientific language for target audiences. Proven experience in reviewing or translating patents or technical documents. Proficiency in using CAT tools like XTM for project management and quality assessment. If this sounds like an opportunity you’d like to jump at, please send us your application.   Job Reference: #LI-JC1

Location: San Francisco, CA About Anthropic 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. About the role Enterprise is central to Anthropic's mission. The organizations that could benefit most from Claude are often the most demanding buyers, with rigorous requirements around security, compliance, and control. We believe earning their trust is essential to ensuring AI benefits the world broadly. We're looking for an engineering manager for our Enterprise pillar —the team that makes Claude enterprise-ready at scale. When a Fortune 500 company wants to roll out Claude to 100,000 employees, we're the team that makes it possible. You'll build the foundational systems that large organizations require before they can deploy AI at scale. This work directly converts product-market fit into revenue by removing the deployment blockers that prevent large organizations from adopting Claude broadly. This role sits at the intersection of enterprise product, platform infrastructure, and go-to-market. You'll partner closely with product, design, sales, and customer success to understand what our largest customers need, then translate those requirements into scalable technical solutions that work across Claude.ai , Claude Code, and API. Responsibilities Lead and develop a team of engineers building out features and foundations that make Claude enterprise-ready at scale Own engineering execution end-to-end: planning, prioritization, delivery quality, team health, and incident response Partner with engineering teams throughout the company to ensure that the platforms we build are extensible and easy to adopt Partner with sales and customer success on enterprise deals—understanding requirements, representing engineering in key conversations, and turning what you learn into priorities Shape the roadmap with product and design, not just execute against it Drive the compliance and platform-readiness work your customers require, partnering with security and legal Recruit, onboard, and grow strong engineers; give direct feedback and build a healthy, high-performing team Minimum qualifications 4+ years of experience as an engineering manager, with experience in enterprise SaaS, cloud services, or admin tools Are comfortable executing at a fast pace to meet the expectations of our customers Are detail-oriented and quality-focused - our customers are using Claude for critical workflows and our product needs to stay robust and reliable Are comfortable working with enterprise customers, working alongside sales and customer success and joining customer conversations Are a skilled engineering manager who treats management as a craft—clear feedback, strong 1:1s, consistent investment in your team's growth Preferred qualifications Experience with AI/ML products and understanding how enterprises evaluate and deploy AI tools Background with compliance frameworks for regulated industries (SOC2, HIPAA) and enterprise audit logging requirements Experience building integrations, permissions, billing, or pricing infrastructure Familiarity with data residency and sovereignty requirements across global regions Startup experience, particularly in scaling enterprise platforms from early adoption to broad deployment Experience in working with research to improve domain specific model capabilities The annual compensation range for this role is listed below. 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. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY About Anthropic 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. About the role Anthropic's Inference organization serves Claude to millions of users and enterprise customers with the speed, reliability, and efficiency that frontier AI demands. We build across GPUs, TPUs, and Trainium, and the complexity of our development environment grows with every platform we add. We're looking for a Staff engineer to be the technical lead for Inference Developer Productivity: the team that makes every engineer in the org dramatically more effective at building, testing, and shipping inference software. This is a senior IC role with broad technical ownership. You'll set technical direction for the team's toolchains, workflows, and feedback loops, and you'll be the one making the hard calls on architecture, prioritization, and tradeoffs across heterogeneous accelerator platforms. You'll pair with the team's Engineering Manager, who owns hiring and people development, while you own the technical roadmap and drive the work. You'll also partner closely with Anthropic's central Infrastructure org, where company-wide developer productivity lives, to make sure Inference's multi-accelerator reality is well served without duplicating effort. This role is for someone who has been the technical anchor on a platform or infrastructure team before, who thinks in systems and feedback loops, and who gets real satisfaction from the moment another engineer stops fighting their environment and starts shipping. Key responsibilities Set technical direction for Inference Developer Productivity, owning the architecture and roadmap for toolchains, dev environments, and CI/CD across GPU (CUDA), TPU, and Trainium platforms Be the technical owner of accelerator toolchain management: compilers, drivers, libraries, frameworks, kept current, compatible, and well-tested so Inference engineers focus on model serving instead of environment archaeology Design and build infrastructure for efficient accelerator usage during development, including devbox environments, pre- and post-land validation automation, and shared tooling that reduces the cost of working across heterogeneous hardware Define and instrument productivity metrics for the Inference org, building the dashboards and alerting that surface regressions early (smoke tests red for extended periods, build times creeping up, toolchain breakages) and drive them to resolution Proactively hunt down bottlenecks, toil, and friction across Inference engineering workflows, then design and build the systems that eliminate them Act as the technical counterpart to Anthropic's central Infrastructure org, aligning on shared developer productivity initiatives, contributing Inference-specific requirements, and making the call on build vs. adopt Mentor engineers on the team through design review, code review, and direct collaboration, raising the technical bar without owning headcount Minimum qualifications 8+ years of software engineering experience, with significant time as the technical lead or anchor on an infrastructure, platform, or developer productivity team Deep background in systems engineering, build/test infrastructure, or ML infrastructure, with the ability to go hands-on with toolchain issues, CI/CD pipelines, and developer workflow optimization Experience owning toolchains or development environments for compute-intensive workloads (ML training or inference, HPC, large-scale distributed systems) Real depth in at least one accelerator ecosystem (CUDA/GPU, TPU, or Trainium/AWS Neuron) and genuine appetite to learn the others A track record of defining and using engineering metrics to drive improvement: you've built dashboards, set SLOs on developer workflows, or led initiatives that measurably improved engineering velocity Experience driving technical alignment across organizational boundaries, advocating for your team's needs while contributing to shared infrastructure Strong written and verbal communication, and the ability to influence technical direction without formal authority Preferred qualifications Experience with ML compiler toolchains (XLA, Triton, NeuronX) or accelerator driver/firmware management at scale Background building or running shared development environments (devboxes, remote development, ephemeral environments) for hardware-dependent workflows Experience with CI/CD systems at scale, particularly for workloads involving accelerator hardware Familiarity with Kubernetes-based development and job scheduling environments Prior tech lead experience on a developer productivity or platform engineering team at a fast-growing AI/ML company The annual compensation range for this role is listed below. 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. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | Seattle, WA About Anthropic 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. About the Role Anthropic's API is the foundation that customers, developers, and our own products build on, and it is scaling fast. We're hiring a Technical Program Manager to drive the scaling and core efficiency programs for the API stack, working at the intersection of the API and the infrastructure it runs on (compute, databases, networking, and inference). Today this work spans many teams and many simultaneous programs, with no single person focused on cohesion across them. You'll be the center: the person who connects isolated workstreams into one coherent roadmap, makes cross-org dependencies visible before they become blockers, and creates clarity on who owns which decisions. Success looks like an API stack that scales efficiently and predictably, with programs that land because someone is accountable for the whole picture. Responsibilities Drive scaling and core efficiency programs for the API stack from architectural direction through sequenced, deliverable execution Run multiple large programs simultaneously across infrastructure, networking, and the API layer Act as the connective tissue between API, infrastructure, database, networking, and inference teams, owning cross-org dependencies end to end Establish decision-making clarity: who owns what, where trade-offs get made, and how isolated streams roll up into one program view Surface risks, progress, and trade-offs to engineering leadership with the right altitude and cadence You may be a good fit if you Have 7+ years of technical program management experience, with a track record of successfully delivering complex, cross-functional programs Have experience with API platforms, distributed systems, and core infrastructure programs and can engage meaningfully with the engineers who design and operate them Have driven scaling, performance, or efficiency programs for high-volume production systems, including the tradeoffs across performance, reliability, and cost Have coordinated programs spanning many partner organizations, managing cross-team dependencies, commitments, and escalations at the working level Are highly organized and can manage multiple parallel workstreams effectively across distributed teams Thrive in unstructured environments with a knack for bringing order to chaos and creating clarity in ambiguous situations, including where decision ownership is unclear Have excellent written and verbal communication skills, with the ability to influence without authority Are passionate about Anthropic's mission and interested in the challenges of operating AI infrastructure safely and reliably The annual compensation range for this role is listed below. 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. Annual Salary: $290,000 — $435,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY About Anthropic 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. About the RL Teams Our Reinforcement Learning teams play a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of our latest Claude models. Our work spans several key areas: Developing systems that enable models to use computers effectively Advancing code generation through reinforcement learning Pioneering fundamental RL research for large language models Building scalable RL infrastructure and training methodologies Enhancing model reasoning capabilities We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish. About the Role We're hiring for the Code RL team within the RL organization. As a Research Engineer, you'll advance our models' ability to write, edit, test, debug, and ship real software — end to end, on real codebases, with real tools — and to do it correctly, fast, and safely. This role blends research and engineering. You'll design RL environments and coding tasks, build the reward signals and verifiers that capture what "good code" means, run training experiments on frontier models, diagnose why a model does (or doesn't) get better at a class of software-engineering work, and improve the speed and reliability of the pipelines that make all of that iterate fast. Code RL spans several focus areas — from agentic coding behaviors and code correctness, to long-horizon autonomous engineering, to high-performance code for accelerators — and we'll match you to the area where you'll have the most impact. You may be a good fit if you: Have strong software-engineering skills and deep Python expertise, including async/concurrent programming Are comfortable owning systems end to end and debugging across the stack Can balance research exploration with engineering implementation, and engage rigorously in shaping experimental design and interpreting results Care about code quality, testing, and performance Are passionate about the potential impact of AI and are committed to developing safe and beneficial systems Strong candidates may also have: Experience with reinforcement learning, RLHF, post-training, or LLM finetuning Built coding agents, code-execution sandboxes, eval harnesses, verifiers, or developer tooling Background in program analysis, testing, verification, compilers, or formal methods Experience with PyTorch and large-scale distributed training; performance profiling and optimization of ML systems CUDA / GPU or TPU kernel experience and accelerator-performance intuition Experience with virtualization and sandboxed code execution environments Related roles If your background leans toward one of these areas specifically, you may also want to look at these postings: Research Engineer, Performance RL (Reinforcement Learning) — teaching Claude to write correct, fast code for accelerators Research Engineer, Universes — long-horizon, ultra-realistic agentic training environments Research Engineer, Cybersecurity RL (Reinforcement Learning) — RL for security-relevant coding capabilities The annual compensation range for this role is listed below. 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. Annual Salary: $500,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA About Anthropic 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. About the role Anthropic is dedicated to developing AI assistants that are helpful, harmless, and honest. As usage of our AI services grows, we need to ensure they are not misused. The Safeguards team is at the forefront of protecting our users from the risks of powerful AIs as well as ethical, technical, and social risks from the use of generative AI. The Safeguards team at Anthropic builds protections for new AI features enabled by the research teams and protects new products and surfaces developed by our product teams. As a Product Manager for the Safeguards team at Anthropic, you will own the ideation, design, development and deployment of Safeguards systems and relevant product UX to ensure we are advancing frontier models safely to users across various cloud platforms. You will work closely with our research and product teams to develop detections, evals, interventions, and tools to measure and mitigate deployment and user risks. We are looking for a product manager who is deeply committed to making AI safe and beneficial for humanity.  You are aware of the risks and are committed to working with experts and coming up with ideas for Anthropic to implement. You have deep technical expertise in development, deployment and measurement of Safeguards systems. You thrive in rapidly moving and ambiguous environments. Responsibilities: Determine how to build in safety by design upstream and leverage downstream defenses for Anthropic’s frontier models, AI products, customers on different surfaces - Claude.ai, 1P API, external Cloud providers. Ability to write safety evals and communicate externally about safety. Drive impact via ruthless prioritization by clearly defining problems, solution options forward, clarity on both business & technical tradeoffs and accordingly clear requirements toward MVP vs. ideal state. Align & collaborate with policy, enforcement, research, engineering and cross functional stakeholders. Understand the AI landscape and ecosystem to plan for mitigation of deployment risks of increasingly powerful models and determined adversaries. Lead the development of metrics to understand the area, performance, blindspots to help inform future project planning. Minimum Qualifications You may be a good fit if you have: Ability to make technical tradeoff decisions; ideally with experience working across policy experts, AI/ML research engineers and software engineering teams to design and build state of the art safety systems. Strong user understanding of how our products are used, their Safeguards concerns and how we provide the best solutions. Demonstrated ability to build product and engineering strategy across multiple cross-functional teams for a rapidly changing space. Demonstrated experience in designing and building metrics to evaluate risks, system performance, user impact and making crisp tradeoffs Very strong ability to navigate, and prioritize amidst rapidly changing product specs, and to flex into different domains to bring clarity and execute. Evidence of exercising judgment and decision making in ambiguous situations. Planning, building, launching and measuring new products / systems in a zero to one environment. Ability to clearly articulate complex technical concepts to non-technical audiences in written and verbal communication. Think creatively about the risks and benefits of new technologies, and think beyond past checklists and playbooks. Preferred Qualifications 5+ years in product management with a focus on fast problem understanding, building roadmaps with tractable progress, ability to get into the details on data, detection & interventions, infrastructure & tools, and/or evals. The annual compensation range for this role is listed below. 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. Annual Salary: $305,000 — $385,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA About Anthropic 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. About the role The Safeguards team is responsible for ensuring our models and products are developed and deployed safely. We're looking for an Engineering Manager to lead our Review Tooling team, which builds the systems that humans — and increasingly Claude — use to investigate potential harms and take enforcement actions across Anthropic's first-party products and third-party cloud platforms. This is a foundational role: you'll own the tools our safety investigators rely on to understand what's happening on our platforms and act on it, as well as the platform underneath those tools. That platform includes analytics capabilities, privacy-preserving primitives that keep review workflows compatible with our data retention commitments, and a sandbox environment where new review interfaces and workflows can be built and iterated quickly. As model capabilities and usage grow, you'll also drive how we scale review through automation — building systems where Claude meaningfully extends what human reviewers can do, while keeping people in the loop where their judgment matters most. You'll partner closely with policy, operations, data science, and legal teams to ensure our enforcement systems are effective, accurate, and trustworthy. Key responsibilities Lead, grow, and develop a team of engineers building investigation, review, and enforcement tooling for both first-party and third-party platform surfaces Define the vision and roadmap for our review tooling platform, including analytics, privacy-compatible data access primitives, and a sandbox for rapidly developing new review interfaces Drive the team's strategy for scaling review through automation, including enabling reviewers to use Claude effectively and building toward Claude-assisted and Claude-driven review workflows Partner with policy, operations, legal, privacy, and data science stakeholders to translate enforcement and investigation needs into reliable, well-designed systems Ensure review tooling evolves alongside new privacy primitives and data retention commitments, so reviewers can do their work without compromising user trust Create clarity for the team and stakeholders in an ambiguous and evolving environment Take an inclusive, equitable approach to hiring and coaching top technical talent, and maintain a high-performing team Contribute to engineering-wide initiatives as a member of Anthropic's engineering management community Minimum qualifications Experience managing software engineering teams, including hiring, coaching, and developing engineers A technical background in full-stack or platform engineering, with the ability to engage deeply in architecture and design discussions Experience shipping internal tools or platforms with demanding operational users, and a track record of improving their workflows measurably Experience working cross-functionally with non-engineering partners such as operations, policy, or legal teams Excellent communication skills, including the ability to explain technical tradeoffs to non-technical stakeholders Care about the societal impacts of AI and want your work to make powerful systems safer Preferred qualifications 4+ years of management experience, 10+ years of industry software engineering experience Experience building trust and safety, integrity, fraud, or abuse-prevention tooling, or other systems supporting human review at scale Experience designing systems under strict privacy, compliance, or data governance constraints, such as zero data retention environments Experience integrating LLMs or agentic systems into operational workflows, or building human-in-the-loop automation Experience building developer platforms or extensible tooling frameworks that other teams build on top of Experience supporting enforcement or moderation systems across multiple product surfaces, including enterprise or cloud platform contexts The annual compensation range for this role is listed below. 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. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | Seattle, WA About Anthropic 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. About the Role Anthropic is investing in shared platform capabilities that power Claude across our consumer and developer products: the common foundation that Claude, Cowork, Claude Code, and future surfaces are built on. We're hiring a Technical Program Manager to be the connective tissue for this effort, someone who ensures we're building the platform the rest of Anthropic's products are built on, and that product teams actually get leverage from it. This is not a single-team TPM role. You'll work across the platform engineering teams and every product team that consumes the platform, driving one cohesive roadmap rather than a collection of disconnected workstreams. Success looks like products at Anthropic shipping more easily, faster, and more reliably because they're built on a common foundation, with developer velocity increasing measurably across the company, not just within one team. Responsibilities Own the cross-Apps platform roadmap end to end: sequencing, dependencies, and tradeoffs across platform teams and the apps teams that depend on them Drive alignment between platform engineering and apps teams so platform investments map to real consumer needs and adoption actually happens (leverage only exists if teams build on the platform) Identify duplication across surfaces and convert it into shared platform capabilities Establish the operating rhythm: planning, status, escalation paths, and launch coordination across orgs Create program documentation including roadmaps, status reports, risk assessments, and communication plans Facilitate technical decision-making by bringing together stakeholders, driving consensus, and ensuring timely resolution of blocking issues You may be a good fit if you Have several years of experience in technical program management, with a track record of successfully delivering complex, cross-functional programs Have experience with platform engineering efforts (shared services, developer platforms, or common capabilities consumed by multiple product teams) and can engage meaningfully with the engineers building them Have driven platform adoption across consuming teams, where success depended on other teams choosing to build on what you shipped Have experience coordinating across multiple engineering teams and organizations simultaneously Are highly organized and can manage multiple parallel workstreams effectively across distributed teams Thrive in unstructured environments with a knack for bringing order to chaos and creating clarity in ambiguous situations Have excellent written and verbal communication skills, with the ability to influence without authority Are passionate about Anthropic's mission and interested in the challenges of bringing AI capabilities to users safely and reliably The annual compensation range for this role is listed below. 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. Annual Salary: $365,000 — $435,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic 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. About the role Our Inference team is responsible for building and maintaining 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. 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. Inference systems are highly performance sensitive distributed systems. Inference serves hundreds of thousands of customers every day, and the size & span of the inference fleet requires sophisticated routing, scaling, and networking systems. Key responsibilities Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide Develop resilient, flexible systems that adapt in real time to real world events Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators Maximize compute efficiency across the fleet by autoscaling and orchestrating production, research, and experimental workloads Build and operate production-grade deployment pipelines for releasing new models to users Provide high-performance inference infrastructure that enables researchers to develop next-generation models Integrate new AI accelerator platforms and support inference for new model architectures Minimum qualifications Significant software engineering experience, particularly with distributed systems Results-oriented, with a bias towards flexibility and impact Willingness to pick up slack, even if it goes outside your job description Desire to learn more about machine learning systems and infrastructure Thrive in environments where technical excellence directly drives both business results and research breakthroughs Care about the societal impacts of your work Preferred qualifications Experience with high-performance, large-scale distributed systems Experience implementing and deploying machine learning systems at scale Experience with load balancing, request routing, or traffic management systems Familiarity with LLM inference optimization, batching, and caching strategies Experience with Kubernetes and cloud infrastructure (AWS, GCP, Azure) Proficiency in Python or Rust Representative projects Designing intelligent routing algorithms that optimize request distribution across many accelerators in different environments Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads Building production-grade deployment pipelines for releasing new models to millions of users reliably Contributing to new inference features Supporting inference for new model architectures Analyzing observability data to tune performance based on real-world production workloads Managing multi-region deployments and geographic routing for global customers Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. 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. Annual Salary: $320,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic 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. About the role We're seeking an experienced software engineer to build the platform behind governance, risk, and compliance (GRC) at Anthropic. Compliance information lives across dozens of systems, from cloud infrastructure and identity providers to HR platforms and code repositories. You'll build the pipelines, integrations, and services that bring that data together and turn it into automated checks, real-time dashboards, and evidence for real time decision making, compliance obligations, and to support expanding the markets we can serve. You will be an early member of the team, collaborating with stakeholders across Security, IT, Engineering, Privacy Engineering, Legal, Finance, and more to turn manual compliance processes into scalable, reliable systems. You will lead your own projects end to end, and you will put Claude to work as an extension of the team through agentic workflows for evidence collection, analysis, and continuous monitoring. If you've built internal platforms, data pipelines, or privacy systems, you'll feel right at home, and you don't need a compliance background to get started. Key responsibilities Design and build data pipelines that aggregate risk, control, and asset information from across Anthropic's technology stack, solving hard integration problems like disparate schemas, inconsistent data quality, and unified views of posture Build and maintain integrations connecting our platform to cloud infrastructure, identity management, HRIS, ticketing, version control, and CI/CD systems to enable automated evidence collection and continuous validation Translate written policies and regulatory requirements into policy-as-code, turning static documents and spreadsheets into enforceable rules, automated checks, and continuous monitoring Design and deploy agentic workflows where Claude handles work that previously required manual effort, such as analyzing evidence, generating audit responses, and monitoring control effectiveness Develop dashboards and reporting that provide real-time visibility into risk and compliance posture for audiences ranging from engineers to executives and external auditors Make architectural decisions that shape how the platform grows, establishing patterns and tooling that other engineers will build on Partner with Security, IT, Infrastructure, and product engineering teams to make controls and evidence collection native to how Anthropic builds and ships Operate what you build, owning reliability and data integrity for systems that audits and executive reporting depend on Minimum qualifications Have 8+ years of experience building backend systems, data pipelines, or internal platforms that other teams depend on, ideally operating at tech lead level Are a systems thinker who understands how data flows between systems, where the integration points are, and what breaks when systems don't talk to each other Have depth in either integration engineering (REST APIs, webhooks, authentication flows, event-driven architectures) or data infrastructure (warehousing, ELT/ETL, orchestration), and fluency in the other Are proficient in Python, Go, or similar languages, and have production experience with cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code Hold a high bar for data quality and reliability, and enjoy turning ambiguous, manual processes into simple, reliable automated systems Take full ownership of your work, from design through deployment and operations, and can navigate ambiguity and make sound technical decisions independently Take a product-focused approach to platform work and care about building tools internal customers love to use Are excited to build with LLMs as system components, designing agentic workflows, evaluating their outputs, and making them reliable enough for high-stakes use Preferred qualifications Experience in domains where engineering meets regulation, such as privacy engineering, data governance, fintech, healthcare, or trust and safety Experience designing and shipping LLM-based or agentic automation in production or operational contexts Familiarity with compliance frameworks (SOC 2, ISO 27001, HIPAA, FedRAMP) or GRC platforms (ServiceNow, Vanta, Drata, OneTrust); this is helpful but not required Prior experience at high-growth startups, building processes and systems that scale The annual compensation range for this role is listed below. 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. Annual Salary: $320,000 — $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic 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. About the role The Security Risk team is responsible for how Anthropic identifies, prioritizes, and drives treatment of its most important security risks. We are rebuilding risk management to operate as an engineering function through automation and AI-native platforms to enable decision making. The systems we assess span Anthropic’s full security landscape, from authorization primitives to cryptographic foundations, so the team needs breadth across domains and the ability to go deep in any of them. Security Risk, in deep partnership with Security Engineering, will help define the security program to shape how both engineers and non-engineers build and ship software. The conventional GRC playbook was not built for a company shipping frontier AI. You will help define what replaces it, with a direct line to CISO-level decisions and the mandate to build the AI-native platform underneath. You’ll work across a breadth of areas from identity and secrets management to infrastructure security, with your focus shaped by your strengths, ability to learn quickly, and the team’s priorities. This is largely greenfield work, and you will help define the architecture and discipline. Key responsibilities Take ownership of Anthropic’s most complex security risk problems and drive them end to end with minimal oversight, turning ambiguous signals into a defensible view of severity and likelihood and seeing them through escalation, treatment decisions, and remediation Build the systems that make risk measurable and let risk work scale, including quantification tooling, automated intake and triage, and the observability that partner teams use to understand their own risk posture Work alongside Security Engineering as a calibrated technical peer who pressure tests architectures and treatment plans, translates findings into prioritized remediation roadmaps, and makes the investment case for what to fix now, what to accept and track, and what to defer Mentor engineers and risk practitioners across Security and the broader engineering organization, and help build a risk engineering culture in which teams own their risks and our team provides the visibility and judgment that supports the Security risk engineering Work across the breadth of Anthropic’s security landscape, spanning areas like identity and secrets management, developer security and supply chain, infrastructure security, and secure frameworks, and build the context needed to reason about risk credibly in each Go deep where a risk demands it, understanding how these systems are built and how they fail so that assessments and treatment plans reflect engineering reality rather than abstraction Risk assessment and quantification Identify systematic risks through threat modeling and structured assessment, then drive the severity calibration and escalation conversations that follow, bringing leadership a defensible position and a clear recommendation that holds up under pointed questions Contribute to the team’s quantitative risk work, applying methods such as calibrated estimation and Monte Carlo simulation where they meaningfully change a resource or treatment decision Risk platform and automation Design and build AI-native risk tooling that uses Claude to classify incoming risks, augment triage, and continuously sense changes in our risk landscape as teams ship Create the dashboards and data pipelines that give engineering and product teams real-time visibility into their risk posture and make distributed ownership of risk practical Remediation strategy and investment Partner with Security Engineering and risk owners to design remediation roadmaps that are explicit about sequencing, ownership, and the investment required Measure outcomes rather than activity, focusing on decisions made and risk reduced Minimum qualifications At least 8 years of software engineering or security engineering experience, including leading and remediating complex security risks independently Bachelor’s degree in a related field or equivalent experience Strong programming skills in Python or at least one systems language such as Go, Rust, or C/C++ Broad knowledge across the core security engineering domains, with depth in at least one, including identity and secrets management, developer security and supply chain, infrastructure and cloud security, and secure frameworks Calibrated risk judgment, meaning you can put a defensible severity and likelihood on an ambiguous problem and change your position when the evidence changes Experience leading cross-functional security initiatives and navigating complex organizational dynamics Outstanding communication skills, translating technical concepts effectively across all levels of the organization A track record of bringing clarity and ownership to ambiguous technical problems and driving them to resolution Low ego and high empathy, with a history of growing the engineers around you and supporting diverse, inclusive teams Passion for AI safety and the role security and risk management play in building trustworthy AI systems Preferred qualifications Owned a named security risk and driven it from discovery through remediation across multiple teams Briefed executives on risk decisions and defended accept, remediate, or transfer recommendations under challenge Built security automation, detection, or risk platforms adopted across an engineering organization Shipped LLM or agent-powered tooling and workflows that automate security or risk activities A security engineering, detection engineering, or offensive security background with a risk-based prioritization mindset Built or operated a quantified security risk program (FAIR-style decomposition, Monte Carlo simulation, loss exceedance analysis) whose outputs changed real resource decisions Enough familiarity with SOC 2, ISO 27001, or FedRAMP to know what compliance does and does not buy you The annual compensation range for this role is listed below. 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. Annual Salary: $320,000 — $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Munich, Germany About Anthropic 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. About the role As an Enterprise Account Executive at Anthropic, you’ll drive adoption of safe, frontier AI by securing strategic deals with top enterprises, unlocking new value streams throughout their business. You’ll leverage your consultative sales expertise to propel revenue growth while becoming a trusted partner to customers, helping them embed and deploy AI while uncovering its full range of capabilities. In collaboration with GTM, product, and marketing teams, you’ll continuously refine our value proposition, sales methodology, and market positioning to ensure differentiated value across the landscape. The ideal candidate will have a passion for developing new market segments, pinpointing high-potential opportunities, and executing strategies to capture them. By driving deployment of Anthropic's emerging products, you will help enterprises obtain new capabilities while also advancing the ethical development of AI. Responsibilities: Win new business and drive revenue for Anthropic. Find your way to the right people at prospective customers, educate them about LLMs, and help them succeed with Anthropic. You’ll own the full sales cycle, from first outbound to launch Design and execute innovative sales strategies to meet and exceed revenue quotas. Analyze market landscapes, trends, and dynamics to translate high-level plans into targeted sales activities, partnerships, and campaigns Spearhead market expansion by pinpointing new customer segments and use cases. Collaborate cross-functionally to differentiate our offerings and sustain a competitive edge Inform product roadmaps and features by gathering customer feedback and conveying market needs. Provide insights that strengthen our value proposition and enhance the customer experience Continuously refine the sales methodology by incorporating learnings into playbooks, templates, and best practices. Identify process improvements that optimize sales productivity and consistency You may be a good fit if you have: 5+ years of enterprise sales experience driving adoption of emerging technologies with a consultative, solutions-oriented sales approach A track record of managing complex sales cycles and securing strategic deals by understanding multifaceted technical requirements and crafting tailored solutions Demonstrated ability to navigate dynamic stakeholder ecosystems, building consensus and providing innovative solutions to disparate groups Extensive experience negotiating highly complex, customized commercial agreements with multiple stakeholders Proven experience exceeding revenue targets in fast-paced organizations by effectively managing an evolving pipeline and sales process Excellent communication skills and the ability to present confidently and build connections across all customer levels, from ICs to C-level executives A knack for bringing order to chaos and an enthusiastic “roll up your sleeves'' mentality. You are a true team player A strategic, analytical approach to assessing markets combined with creative, tactical execution to capture opportunities A passion for and/or experience with advanced AI systems. You feel strongly about ensuring frontier AI systems are developed safely The annual compensation range for this role is listed below. 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. Annual Salary: €205.000 — €255.000 EUR Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY About Anthropic 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. About the role As the VC Partnerships Lead at Anthropic, you will drive transformative growth and strategic alignment by forging and managing high-impact startup partnerships. You will drive the adoption of Anthropic's cutting-edge AI capabilities within the startup ecosystem. In this role, you will design and execute innovative programs that enable startups to easily access and utilize Anthropic's advanced AI models. Your goal will be to scale our reach and impact by engaging with startups directly and through the accelerator ecosystem. This is an individual contributor role with broad ownership — you'll operate with high autonomy, partnering closely with sales, marketing, and product teams to build and run our startup partnerships motion. Key responsibilities Develop and lead Anthropic's startup partnerships strategy, leveraging our AI technology and industry partnerships Build relationships with key VC firms, and entrepreneurial communities Create compelling startup-focused offerings, programs, and growth initiatives Cultivate strong relationships with current and new accelerator partnerships; build out relationship models, own touch points, and drive outcomes such that accelerator portfolio companies are choosing to build on Claude Plan and execute startup-focused events, campaigns, and promotions to drive awareness and adoption Gather product feedback and represent the needs of the startup community to inform Anthropic's product roadmap Track and report on key metrics to measure the success and ROI of startup initiatives Minimum qualifications Have 7+ years of experience in partnerships, founder/operator roles, growth, or technical GTM roles—we're looking for builders Have a deep understanding of the startup ecosystem and AI/ML technology landscape—can speak credibly about technical products to technical audiences Have built relationships with VCs, worked at a VC firm, or successfully partnered with accelerators to drive portfolio engagement Excel at 0-to-1 program building—comfortable building from scratch, wearing multiple hats, and scaling based on data Proven ability to develop and execute complex, cross-functional go-to-market programs Possess exceptional communication skills—outstanding writer who crafts narratives for founders, developers, and VCs Thrive in fast-paced environments with bias to action and comfort with ambiguity BA/BS degree or equivalent practical experience Preferred qualifications Founded a company or led product at a high-growth startup Direct experience working for or with venture capital firms like Y Combinator, Lightspeed Ventures, Accel, a16z, Sequoia Capital Technical background—former developer, PM with hands-on coding experience, or deep familiarity with AI/ML development workflows Developer advocate or developer relations background with active presence in technical communities Familiarity with large language models and their applications in generative AI Existing relationships with venture capital firms, startup accelerators, and entrepreneurial communities The annual compensation range for this role is listed below. 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. Annual Salary: $215,000 — $300,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Tokyo, Japan About Anthropic 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. About the role As an Enterprise Account Executive for Digital Native Business based in Tokyo, you'll drive the adoption of safe, frontier AI technology across Japan's fastest-moving technology companies. This is a greenfield, new business role: you'll build your territory from the ground up, owning the full sales cycle from first outbound touch to close across Japan's internet services, gaming, e-commerce, SaaS, fintech, and media companies. You'll work directly with founders, technical leaders, and product teams to help them build with Anthropic's AI as a core part of their products and operations. Key responsibilities Own and exceed revenue targets by winning net-new logos across Japan's digital native companies, including internet services, gaming, e-commerce, SaaS, fintech, and media Build a greenfield territory from scratch: develop your own account list, generate pipeline through self-sourced outbound prospecting, and create repeatable plays for landing new accounts Run fast, consultative sales cycles with founders, CTOs, CPOs, VPs of Engineering, and Heads of AI, positioning Claude as the foundation for AI-powered products and competitive differentiation Land new accounts quickly and set them up for expansion, working closely with technical buyers and developer teams who evaluate hands-on Orchestrate internal teams (Product, Engineering, Applied AI, Partnerships) to win technical evaluations and accelerate time to production for customers building on our models Preferred qualifications 8+ years of sales experience in Japan with a clear track record as a hunter: consistently winning net-new logos and generating the majority of your own pipeline through outbound prospecting Experience selling to digital native, internet, or high-growth technology companies, and comfort engaging technical buyers such as engineering and product leaders, not just business stakeholders A track record of opening greenfield territories or segments with little existing brand presence, building pipeline and closing revenue from zero Proven experience exceeding revenue targets driven primarily by new business, with the ability to manage high-velocity cycles alongside larger strategic deals Strong commercial instincts for usage-based and consumption models, and the ability to connect product adoption to revenue growth A knack for bringing order to chaos and an enthusiastic "roll up your sleeves" mentality. You are a true team player who thrives in ambiguous, startup-like environments A strategic, analytical approach to territory and account prioritization combined with high-energy, persistent execution A passion for and/or experience with advanced AI systems. You feel strongly about ensuring frontier AI systems are developed safely and responsibly for broad benefit Excellent communication skills in both Japanese and English What we offer Competitive base salary and commission structure commensurate with experience Equity participation Comprehensive benefits package Hybrid work model with flexibility Access to cutting-edge AI technology and world-class research team Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY About Anthropic 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. About the Role As Data Operations Manager, you'll build and scale data operations across research teams working on frontier AI capabilities. You'll partner with researchers to design and execute data strategies, manage vendor relationships, and own the entire data pipeline from requirements to production. This role requires operational excellence combined with technical depth to understand what makes high-quality training data, but your focus will be on strategy and execution. About the Impact The data operations you build will directly determine how well our models perform on critical capabilities—tool use accuracy, prompt injection robustness, long-horizon reasoning, and safety alignment. You'll work with world-class researchers advancing the frontier while building the operational infrastructure to scale these efforts. We're looking for someone who gets excited about the challenge of scaling quality across diverse research areas—someone who can understand nuanced technical requirements, build the right partnerships, and execute flawlessly. If you thrive at the intersection of operational excellence and cutting-edge AI research, we'd love to hear from you. Responsibilities: Own and execute data strategy for research teams advancing frontier AI capabilities across RLHF, safety, tool use, and agentic workflows Drive strategic vendor partnerships and build scalable frameworks for technical data collection at scale Design and implement operational systems that translate research requirements into high-quality data pipelines Build evaluation frameworks and quality standards that ensure data meets the bar for training state-of-the-art AI systems Lead cross-functional initiatives to optimize research velocity while maintaining rigorous quality standards Proactively identify risks, bottlenecks, and opportunities to improve efficiency and effectiveness across data operations Partner with senior research leaders to align data operations with model development roadmaps and strategic priorities You may be a good fit if you: Have 3+ years in operations, consulting, product management, or program management roles Have exceptional project management skills with ability to handle multiple complex projects simultaneously Have strong communication skills and can engage effectively with technical and non-technical stakeholders Are familiar with how LLMs work or have strong interest in understanding AI training methodologies Are highly organized and can navigate ambiguity effectively Have experience with data analysis tools (SQL, Python, Tableau, spreadsheets, or similar) Thrive in fast-paced research environments with shifting priorities Are passionate about AI safety and understand the critical importance of high-quality data Strong candidates may also have: Experience with data collection, labeling, or annotation operations for AI/ML systems Knowledge of RLHF, constitutional AI, or human-in-the-loop workflows Background working with research teams at AI companies or research-oriented organizations Experience managing vendor relationships or external contractors Consulting background with experience translating complex requirements into deliverables Track record of implementing process improvements or quality control systems at scale The annual compensation range for this role is listed below. 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. Annual Salary: $270,000 — $365,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA About Anthropic 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. We're seeking an exceptional Research Scientist to join our Life Sciences team at Anthropic. Our team is building a world-class research group focused on making Claude a superhuman life sciences research assistant. This role sits at the intersection of machine learning, software engineering, and biology — you'll directly improve model capabilities on scientific tasks through post-training, evaluation design, and RL environment development. As a core member of our Life Sciences team, you'll work in a high-impact team that translates deep biological domain knowledge into model training objectives, benchmarks, and agentic workflows. You'll help establish Anthropic as a leader in AI-accelerated biology while shaping how frontier models reason about and execute computational biology tasks. This role offers a unique opportunity to shape how frontier AI models learn to do biology. You'll work alongside some of the world's best AI researchers while tackling problems that matter for human health and scientific understanding. If you're excited about turning your computational biology expertise into model capabilities, we want to hear from you. Key Responsibilities Build and ship agentic tools and integrations that let Claude execute real life science workflows — bioinformatics pipelines, database queries, analysis notebooks, literature review Design and build evaluation benchmarks that measure model capabilities on biology tasks — figure interpretation, bioinformatics, protocol reasoning, literature synthesis Work closely with product and design teams to scope, prototype, and ship features for life sciences users Partner with external biotech, pharma, and academic users to understand their workflows and turn feedback into product improvements Build and maintain the engineering infrastructure behind our biology product surface — tool scaffolding, data pipelines, eval harnesses Translate biological domain knowledge into product requirements and evaluation criteria that guide model improvement Minimum Qualifications Experience applying ML and software engineering to biological problems — computational biology, bioinformatics, protein ML, genomics, or similar Experience working in drug discovery or development at a biotech or pharma company, or conducted fundamental research in an academic setting — with an understanding of what real scientific workflows look like and where they break down Strong software engineering skills: comfortable building production-quality Python, working in large codebases, and owning infrastructure end-to-end Hands-on experience training or fine-tuning ML models (LLMs, protein language models, or other deep learning architectures) A track record of shipping computational tools or pipelines that biologists actually use Comfortable navigating ambiguity and defining problems in a rapidly evolving research environment Able to work independently while collaborating tightly with research, product, and domain-expert teams Results-oriented with a bias toward rapid iteration and measurable impact Passionate about using AI to accelerate scientific discovery while maintaining high ethical standards Preferred Qualifications 5+ years of experience applying ML and software engineering to biological problems — computational biology, bioinformatics, protein ML, genomics, or similar Ph.D. in computational biology, bioinformatics, bioengineering, CS, or a related quantitative field — or equivalent industry experience Experience with LLM post-training: RLHF, RL from verifiable rewards, SFT data curation, or eval-driven development Direct experience with therapeutic discovery pipelines — target identification, lead optimization, ADMET modeling, or clinical data analysis Familiarity with bioinformatics tooling and pipelines (sequence analysis, structure prediction, single-cell, variant calling, etc.) Experience building agentic systems or tool-use environments Published research in ML for biology, or open-source contributions to computational biology tools Fluency with biological databases (UniProt, PDB, Ensembl, NCBI) and the ability to reason about their schemas and failure modes The annual compensation range for this role is listed below. 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. Annual Salary: $300,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic 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. About the role The Computer Use team teaches Claude to see and operate computer interfaces, and builds the agent harness and end-user products that turn that capability into real tools. The team sits inside Anthropic's research organization and closes the loop between product and model. As a Product Engineer on this team, you'll own end-to-end delivery of our computer-use and browser-control product surfaces. You'll build across the full stack, from the user interface to the agent runtime to the backend services behind it. You'll work directly alongside researchers, with no layers between you and the model or the user. This is a dynamic role in which priorities evolve frequently. Success depends on a high tolerance for ambiguity, the adaptability to shift focus as needs change, and the agility and discernment to continuously prioritize the highest impact work. Key responsibilities Own end-to-end delivery of computer-use and browser-control product surfaces: scope, build, ship, measure, and iterate Diagnose and resolve reliability and robustness issues in the computer-use agent harness that block real-world usage Partner with computer-use researchers Partner with the Claude Cowork team on shared surfaces, integrations, and knowledge-worker workflows Instrument products and use usage data to drive prioritization and measure progress Translate fuzzy user pain points into concrete, shippable features for knowledge workers Minimum qualifications Experience building and shipping a product from zero to one with end-to-end ownership, as a founding or early engineer at a startup or with equivalent ownership inside a larger company Strong full-stack engineering skills, including production web frontend and backend development Hands-on experience building with LLM APIs, prompting, or agent frameworks A track record of shipping to external users and iterating based on their feedback Preferred qualifications Strong product design instincts and the ability to produce a clean, usable interface without a dedicated designer Experience with browser automation, desktop automation, or robotic process automation systems Experience building evals or quality harnesses for machine learning systems Comfort with lightweight data analysis, such as SQL, notebooks, and defining and tracking product metrics Experience designing agent loops, tool integrations, or guardrails for LLM-based systems Representative projects Own and resolve the top reliability and robustness issues on the computer-control and browser-control product surfaces, with measurable improvement in task success rate Take a net-new computer-use powered workflow from concept to external users, including instrumentation and a readout on usage The annual compensation range for this role is listed below. 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. Annual Salary: $300,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: New York City, NY; San Francisco, CA; Seattle, WA About Anthropic 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. About the role As an early member of our Safeguards Data Science and Analytics team, you will play an instrumental role in our company’s mission of building safe and beneficial artificial intelligence by building and scaling a data driven culture from the ground up. In this unique company, technology, and moment in history, your work will be critical to informing our product and commercial strategy as we deploy safe, frontier AI at scale to the world. You will work closely with product, engineering, policy & enforcement to define and measure key company success metrics, analyze user behavior to identify new enforcement opportunities and build a culture of developing and testing hypotheses through experimentation. You’ve worked in cultures of excellence in the past, and are eager to apply that experience to building robust and scalable systems and processes as our company goes through a phase of rapid growth. Key responsibilities Deep dive into user behavior data to provide insights on safety concerns Define core metrics that measure the team's success. Set goals, build forecasts, monitor performance, and develop actionable reporting Identify and size opportunities to improve the product, influencing product roadmap through your insights and recommendations Develop hypotheses on product changes, design controlled experiments, analyze the results, and make recommendations based on impact to key metrics Build a data driven culture from the ground up by establishing foundational data best practices and making data more accessible across the company Minimum qualifications Expertise in Python, SQL, and data visualization tools. A bias for action and urgency, not letting perfect be the enemy of the effective. A strong disposition to thrive in ambiguity, taking initiative to create clarity and forward progress. A deep curiosity and energy for pulling the thread on hard questions. Experience in turning open questions and data into concise and insightful analysis. Highly effective written communication and presentation skills. A passion for the company's mission of building helpful, honest, and harmless AI. Preferred qualifications 8+ years of experience in data science or analytics roles, preferably in an infrastructure or operations context. 3+ years of experience deeply embedding in Product teams. Experience working on safety, anti-abuse, integrity shaped problems. Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. 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. Annual Salary: $285,000 — $380,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position 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. 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. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.