Anthropic

<div><h2><strong>About Anthropic</strong></h2>
<p>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.</p></div><h2><strong>About the RL teams</strong></h2>
<p>Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Fable 5.1 and Claude Opus 5.5. Our work spans several key areas:</p>
<ul>
<li>Developing systems that enable models to use computers effectively</li>
<li>Advancing code generation through reinforcement learning</li>
<li>Pioneering fundamental RL research for large language models</li>
<li>Building scalable RL infrastructure and training methodologies</li>
<li>Enhancing model reasoning capabilities</li>
</ul>
<p>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 implementing 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.</p>
<h2><strong>About the role</strong></h2>
<p>We're hiring for the Code RL team within the RL organization. As a Research Engineer, you'll advance our models' ability to design silicon. Hardware design is difficult and unforgiving – exactly the sort of domain we want Claude to excel at.</p>
<p>You'll leverage your chip design expertise and turn it into tasks and signals for models to learn from. Specifically, you will:</p>
<ul>
<li>Invent, design, and implement RL environments and evaluations for agentic RTL generation, design (including formal) verification, physical design optimization.</li>
<li>Work on cross-cutting RL considerations such as EDA-tool latency optimization and proxy rewards.</li>
<li>Conduct experiments and shape our roadmap.</li>
<li>Deliver your work into research and production training runs.</li>
<li>Collaborate with other researchers and engineers across and outside Anthropic.</li>
</ul>
<p>You may be a good fit if you:</p>
<ul>
<li>Have expertise in ASIC or FPGA design: RTL, design verification (UVM, formal methods, coverage-driven), physical design (synthesis, place-and-route, timing closure), PPA optimization, DFT, ECOs.</li>
<li>Are fluent with industry EDA tools and processes.</li>
<li>Have taped out chips and have experience going from spec to silicon.</li>
<li>Know how to balance research exploration with engineering implementation.</li>
<li>Are passionate about AI's potential and committed to developing safe and beneficial systems.</li>
</ul>
<p>Strong candidates may also have:</p>
<ul>
<li>Experience with reinforcement learning, evaluations or environments.</li>
<li>Built tooling or automation around chip design flows.</li>
<li>Worked on ML accelerators or high-performance compute hardware.</li>
<li>Familiarity with high-level synthesis or architecture simulators.</li>
</ul><div><div><div><p>The annual compensation range for this role is listed below. </p>
<p>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.</p></div><div>Annual Salary:</div><div><span>$500,000</span><span>—</span><span>$850,000 USD</span></div></div></div><div><h2><strong>Logistics</strong></h2>
<p><strong>Minimum education: </strong>Bachelor’s degree or an equivalent combination of education, training, and/or experience</p>
<p><strong>Required field of study: </strong>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><strong>Minimum years of experience: </strong>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><strong>Location-based hybrid policy:</strong> 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.</p>
<p><strong>Visa sponsorship:</strong> 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.</p>
<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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.<br /><br /><strong>Your safety matters to us.</strong> 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 <u><a href="http://anthropic.com/careers" target="_blank" rel="noopener noreferrer ugc">anthropic.com/careers</a></u> directly for confirmed position openings.</p>
<h2><strong>How we're different</strong></h2>
<p>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.</p>
<p>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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2><strong>Come work with us!</strong></h2>
<p>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. <strong>Guidance on Candidates' AI Usage:</strong> Learn about <a href="https://www.anthropic.com/candidate-ai-guidance" target="_blank" rel="noopener noreferrer ugc">our policy</a> for using AI in our application process.</p></div>

Research Engineer, Chip Design RL

<div><h2><strong>About Anthropic</strong></h2>
<p>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.</p></div><h2>About the role</h2>
<p>Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. At frontier scale, an RL run is a large distributed system: training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts. As an engineer in RL Engineering, you'll work on keeping that system secure as it scales.</p>
<p>This is a hands-on engineering role. You'll work in the RL codebase and the infrastructure underneath it, alongside the engineers and researchers who build and use it. The system is large and changes as fast as the research does, so security work here has to keep up with that pace without costing performance or velocity.</p>
<p>We're hiring from two backgrounds: security engineers who want to work on large-scale ML systems, and ML systems or research engineers who want to work on security. Strong candidates have depth in one and real interest in the other.</p>
<h2>Key responsibilities</h2>
<ul>
<li>
<p>Design, build, and operate security controls for RL training systems and the infrastructure they run on</p>
</li>
<li>
<p>Work across the stack (orchestration, environments, training, inference) wherever the work is needed</p>
</li>
<li>
<p>Review designs and code across the RL stack, find security problems, and fix them</p>
</li>
<li>
<p>Build shared libraries and tooling that other RL engineers and researchers build on</p>
</li>
<li>
<p>Build the observability needed to understand what these systems are doing</p>
</li>
<li>
<p>Work with researchers and performance engineers to make sure security changes preserve training correctness and performance</p>
</li>
<li>
<p>Write clear design documents for what you build</p>
</li>
</ul>
<h2>Minimum qualifications</h2>
<ul>
<li>
<p>Strong software engineering skills in Python and at least one systems language such as Rust, C++, or Go</p>
</li>
<li>
<p>Experience designing, building, and operating large-scale distributed systems or security systems in production</p>
</li>
<li>
<p>Strong understanding of security fundamentals</p>
</li>
<li>
<p>Working knowledge of Linux, containers, and cloud infrastructure</p>
</li>
<li>
<p>Experience debugging complex problems across many hosts and services</p>
</li>
<li>
<p>Ability to reason about tradeoffs between security, performance, and reliability</p>
</li>
<li>
<p>Strong written communication, including design documents</p>
</li>
</ul>
<h2>Preferred qualifications</h2>
<ul>
<li>
<p>Experience running ML training or inference infrastructure at scale</p>
</li>
<li>
<p>Experience with infrastructure security, such as isolation, access control, networking, or identity</p>
</li>
<li>
<p>Experience with container orchestration such as Kubernetes, and with sandboxed or virtualized code execution at scale</p>
</li>
<li>
<p>Experience building observability for large fleets</p>
</li>
<li>
<p>Experience supporting research teams or other fast-moving internal users</p>
</li>
<li>
<p>Familiarity with reinforcement learning or large language model training workloads</p>
</li>
</ul><div><div><div><p>The annual compensation range for this role is listed below. </p>
<p>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.</p></div><div>Annual Salary:</div><div><span>$320,000</span><span>—</span><span>$405,000 USD</span></div></div></div><div><h2><strong>Logistics</strong></h2>
<p><strong>Minimum education: </strong>Bachelor’s degree or an equivalent combination of education, training, and/or experience</p>
<p><strong>Required field of study: </strong>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><strong>Minimum years of experience: </strong>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><strong>Location-based hybrid policy:</strong> 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.</p>
<p><strong>Visa sponsorship:</strong> 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.</p>
<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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.<br /><br /><strong>Your safety matters to us.</strong> 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 <u><a href="http://anthropic.com/careers" target="_blank" rel="noopener noreferrer ugc">anthropic.com/careers</a></u> directly for confirmed position openings.</p>
<h2><strong>How we're different</strong></h2>
<p>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.</p>
<p>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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2><strong>Come work with us!</strong></h2>
<p>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. <strong>Guidance on Candidates' AI Usage:</strong> Learn about <a href="https://www.anthropic.com/candidate-ai-guidance" target="_blank" rel="noopener noreferrer ugc">our policy</a> for using AI in our application process.</p></div>

Security Engineer / Research Engineer, RL Security

<div><h2><strong>About Anthropic</strong></h2>
<p>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.</p></div><h2>About the role</h2>
<p>Anthropic is looking for a Staff+ Software Engineer to work on the vector search infrastructure behind Claude. Retrieval is how Claude learns about the world. Web search across claude.ai, the API and agentic surfaces, memory across conversations, and the reinforcement learning workloads that train our next models all depend on fast, cheap, high-recall nearest-neighbor search over billions of vectors.</p>
<p>You'll join a small team responsible for the vector database layer that serves Claude's retrieval workloads: its architecture, performance, scalability and cost. This is a foundational role. The team is small, core architectural decisions are still open, and the engineers who join now will shape how the system evolves.</p>
<p>The role sits in our Databases organization and works day to day with the Search Platform team, which owns web search indexing, retrieval and serving, and the Memory &amp; Search team, which owns search and memory inside claude.ai. </p>
<p>We're looking for someone who has built vector or search systems that ran in production, at scale, with real users and a real on-call. You'll be hands-on in the code, and you'll also be the person deciding how the pieces fit together.</p>
<h2>Key responsibilities</h2>
<ul>
<li>Own the core of Anthropic's vector database layer: index structures, storage layout, query execution and the serving layer</li>
<li>Own production readiness - benchmarking against exact search, capacity planning, onboarding new workloads, and the operational tooling to run it at scale</li>
<li>Drive the recall, latency and cost trade-offs - quantization, filtered search, index build and refresh strategy, and how compute and storage are separated and scaled</li>
<li>Scale throughput by an order of magnitude as research and training demand grows, and work out whether the bottleneck is architecture, hardware or engineering bandwidth</li>
<li>Extend the retrieval stack toward hybrid retrieval - lexical search and fused ranking alongside vector search</li>
<li>Set the evaluation methodology for the system -  recall targets, latency objectives, cost per query, and the regression detection that keeps them honest</li>
<li>Set technical direction for a growing team - lead design reviews, make architectural decisions others build on, and mentor the engineers joining the effort</li>
<li>Share the on-call for the systems you own</li>
</ul>
<h2>Minimum qualifications</h2>
<ul>
<li>Direct experience building a vector database or approximate nearest-neighbor search system that ran in production at scale</li>
<li>Deep knowledge of ANN index structures (graph-based, clustering-based or disk-resident approaches), vector quantization and filtered search</li>
<li>Experience with search relevance and ranking</li>
<li>Strong systems programming skills in a language such as Rust, C++ or Go, including performance-critical and memory-intensive code</li>
<li>Experience designing and operating large-scale distributed storage or serving systems with strict latency and reliability requirements</li>
<li>A track record of independently scoping and delivering ambiguous, multi-quarter technical projects</li>
<li>Strong written and verbal communication, with experience driving alignment across teams with different priorities</li>
<li>Interest in AI safety and Anthropic's mission</li>
</ul>
<h2>Preferred qualifications</h2>
<ul>
<li>Experience with object-storage-backed or disaggregated compute and storage database designs</li>
<li>Experience building or operating full-text search engines (inverted indexes, BM25) or hybrid retrieval systems</li>
<li>Familiarity with embedding models and the retrieval demands of LLM training and inference</li>
<li>Experience using GPUs or other accelerators for index build or search</li>
<li>Prior experience as a technical lead on a database or search infrastructure team</li>
</ul><div><div><div><p>The annual compensation range for this role is listed below. </p>
<p>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.</p></div><div>Annual Salary:</div><div><span>$320,000</span><span>—</span><span>$485,000 USD</span></div></div></div><div><h2><strong>Logistics</strong></h2>
<p><strong>Minimum education: </strong>Bachelor’s degree or an equivalent combination of education, training, and/or experience</p>
<p><strong>Required field of study: </strong>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><strong>Minimum years of experience: </strong>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><strong>Location-based hybrid policy:</strong> 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.</p>
<p><strong>Visa sponsorship:</strong> 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.</p>
<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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.<br /><br /><strong>Your safety matters to us.</strong> 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 <u><a href="http://anthropic.com/careers" target="_blank" rel="noopener noreferrer ugc">anthropic.com/careers</a></u> directly for confirmed position openings.</p>
<h2><strong>How we're different</strong></h2>
<p>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.</p>
<p>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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2><strong>Come work with us!</strong></h2>
<p>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. <strong>Guidance on Candidates' AI Usage:</strong> Learn about <a href="https://www.anthropic.com/candidate-ai-guidance" target="_blank" rel="noopener noreferrer ugc">our policy</a> for using AI in our application process.</p></div>

Staff+ Software Engineer, VectorDB

<div><h2><strong>About Anthropic</strong></h2>
<p>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.</p></div><h2><strong>About the role</strong></h2>
<p>Anthropic's customer-facing teams are often the first place a customer sees what Claude can do. As a Demo Engineer, you'll build the demos, reference implementations, and reusable tooling that help those teams make new capabilities tangible, relevant, and trustworthy, ideally within days of a product launch rather than weeks after.</p>
<p>This role sits between product engineering, technical storytelling, and GTM execution. You'll own ambiguous, high-leverage problems end to end: prototyping an agentic experience for a new capability, then hardening it into something reliable that other teams can run on their own. You'll work closely with Product, Engineering, Marketing, Operations, and our sales and solutions teams, and you'll bring what you learn from customer-facing work back to the people building the products.</p>
<p>Because a demo is frequently someone's first impression of what our models can and can't do, accuracy and honesty matter as much as polish. Success in this role looks like customer-facing teams demonstrating new capabilities sooner and with more confidence, recurring requests becoming reusable assets rather than one-off projects, and field insights shaping product and launch-readiness decisions.</p>
<h2><strong>Responsibilities</strong></h2>
<ul>
<li>Own demo readiness for new and priority Claude capabilities, including environments, integrations, synthetic data, evaluations, reliability checks, and fallback paths</li>
<li>Build prototypes, agents, and reference flows that make complex capabilities concrete and tie them to clear customer outcomes</li>
<li>Turn recurring requests into reusable accelerators such as companion apps, templates, Skills, plugins, and self-service demo packages that scale across customer-facing teams</li>
<li>Partner with GTM colleagues on high-impact customer moments, unblock critical technical gaps, and spot the patterns worth turning into shared assets</li>
<li>Build internal agentic systems that automate demo preparation, validation, and asset maintenance, so demos stay current as products change</li>
<li>Translate patterns from customer-facing work into product feedback, launch-readiness priorities, and systemic improvements with Product and Engineering</li>
<li>Define and raise the bar for demo quality across accuracy, safety, reliability, usability, and adoption</li>
<li>Decide when a customer need calls for a bespoke build and when it should become a shared capability</li>
</ul>
<h2><strong>You may be a good fit if you have</strong></h2>
<ul>
<li>Proficiency in Python or TypeScript, with experience shipping working software end to end</li>
<li>Hands-on experience building applications or agents on top of LLM APIs, including prompting, tool use, and retrieval</li>
<li>Experience designing integrations with third-party APIs, data sources, and services</li>
<li>The ability to take an ambiguous capability or customer need to a working prototype quickly, and then make it reliable</li>
<li>Clear communication of technical concepts to both technical and non-technical audiences, including sales and solutions teams</li>
<li>Comfort collaborating across Product, Engineering, Marketing, Operations, and GTM teams</li>
<li>Experience in a demo engineering, solutions engineering, sales engineering, forward deployed engineering, developer relations, or product engineering role</li>
<li>A track record of building reusable internal tools, templates, or self-service assets that other teams adopted</li>
<li>Hands-on experience with Claude Code, the Claude Agent SDK, the Model Context Protocol (MCP), Skills, or plugins</li>
<li>Experience building evaluation or validation harnesses for AI systems, including reliability checks and graceful fallbacks</li>
<li>Experience building always-on or scheduled agentic systems that automate internal workflows</li>
<li>Experience building synthetic or sanitized datasets that make demos realistic without exposing sensitive information</li>
<li>Front-end or product design skills that help demos feel polished and intuitive</li>
<li>Experience supporting product launches or running launch-readiness programs</li>
<li>A history of turning field feedback into concrete product input that influenced a roadmap</li>
<li>A passion for making powerful technology safe and beneficial, and a commitment to representing model capabilities accurately and honestly</li>
</ul><div><div><div><p>The annual compensation range for this role is listed below. </p>
<p>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.</p></div><div>Annual Salary:</div><div><span>$240,000</span><span>—</span><span>$315,000 USD</span></div></div></div><div><h2><strong>Logistics</strong></h2>
<p><strong>Minimum education: </strong>Bachelor’s degree or an equivalent combination of education, training, and/or experience</p>
<p><strong>Required field of study: </strong>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><strong>Minimum years of experience: </strong>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><strong>Location-based hybrid policy:</strong> 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.</p>
<p><strong>Visa sponsorship:</strong> 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.</p>
<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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.<br /><br /><strong>Your safety matters to us.</strong> 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 <u><a href="http://anthropic.com/careers" target="_blank" rel="noopener noreferrer ugc">anthropic.com/careers</a></u> directly for confirmed position openings.</p>
<h2><strong>How we're different</strong></h2>
<p>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.</p>
<p>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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2><strong>Come work with us!</strong></h2>
<p>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. <strong>Guidance on Candidates' AI Usage:</strong> Learn about <a href="https://www.anthropic.com/candidate-ai-guidance" target="_blank" rel="noopener noreferrer ugc">our policy</a> for using AI in our application process.</p></div>

Applied AI Demo Engineer

<div><h2><strong>About Anthropic</strong></h2>
<p>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.</p></div><h2>About the role</h2>
<p>Anthropic is looking for Software Engineers to join the Memory &amp; Search team. We own how Claude remembers you and how it finds what it needs, across Claude.ai, Cowork and Claude Code. That spans the user-facing experience (what Claude remembers, how people see and edit it, how search surfaces the right conversation) and the shared infrastructure underneath it, the memory service, indexing, retrieval and vector search.</p>
<p>Memory is one of the biggest levers on whether Claude feels like it knows you. We recently moved memory from a periodically synthesized summary to a dynamic, editable, on-demand system, and then unified it so the same memory follows you across products. Search went from a top user complaint to something people rely on to find past work. The platform is now in place, and the next phase is finding the product form factors that make memory the most compelling and sticky part of using Claude.</p>
<p>That is why we are hiring product engineers. The team is strong on infrastructure, and we want people who have shipped user-facing products at scale, have a sharp sense for what makes a product feel good, and have built agentic systems where the model, the tools and the user interface have to work together. You will run short, demo-driven experiments on top of the memory and search stack, decide what to keep based on real usage, and help the whole team think like a product team. If you have founded a company, been an early engineer at a startup, or taken a product from zero to one, you will recognize the way we want to work.</p>
<p>This is a trust-sensitive surface. Memory touches privacy, consent and enterprise controls, so you will work closely with product, design, privacy, legal and safeguards, and you will be expected to treat those constraints as part of good product design rather than obstacles to it.</p>
<h2>Key responsibilities</h2>
<ul>
<li>Design, build and ship memory and search experiences in Claude.ai, Cowork and Claude Code, owning them end to end from the backend service through the model's tools to the user interface</li>
<li>Run product experiments on the memory and search stack: form a hypothesis, build a demo, put it in front of real users, measure, and make a clear persevere-or-pivot call</li>
<li>Shape how Claude uses memory and retrieval inside its agentic loop, including what the model stores, when it searches, how results are ranked and presented, and how the user stays in control</li>
<li>Define and track the metrics that tell us whether memory is actually making Claude more useful, and build the evaluations that keep quality honest as the system evolves</li>
<li>Improve search relevance and recall across conversations and memories, working across embeddings, hybrid retrieval and ranking as well as the interface that presents results</li>
<li>Partner with product, design, privacy, legal and safeguards to ship features that respect user consent and enterprise requirements such as customer-managed encryption keys and data retention policies</li>
<li>Raise the bar on product quality for the team through design reviews, code reviews and the standards you set for latency, polish and reliability<br />Share the on-call for the systems you own</li>
</ul>
<h2>Minimum qualifications</h2>
<ul>
<li>Experience building and operating user-facing products used by a large number of people, including the backend services behind them</li>
<li>Experience building agentic systems or LLM-powered products, including tool use, retrieval and prompt or context design</li>
<li>Strong programming skills in Python and TypeScript, with experience across backend services and web front ends</li>
<li>A track record of taking a product or feature from an idea to launch, and iterating on it based on usage data and user feedback</li>
<li>Experience defining product metrics and running experiments to make decisions</li>
<li>Strong product judgment: you notice when something feels off and you fix it, and you can explain why a design choice matters to users</li>
<li>Strong written and verbal communication, with experience working closely with product managers, designers and non-engineering partners</li>
<li>Interest in AI safety and Anthropic's mission</li>
</ul>
<h2>Preferred qualifications</h2>
<ul>
<li>Experience as a founder, early-stage engineer, or someone who has taken a product from zero to one</li>
<li>Experience building search or retrieval systems: embeddings, vector search, hybrid lexical and semantic retrieval, or ranking</li>
<li>Experience building evaluations for LLM or ML systems, or measuring the quality of retrieval and ranking</li>
<li>Experience on consumer products with strong retention, or on personalization systems</li>
<li>Experience shipping features that handle sensitive data or meet enterprise requirements such as customer-managed encryption keys, data residency or HIPAA</li>
<li>Experience with latency-sensitive, performance-critical product work</li>
<li>Experience mentoring engineers or setting technical direction for a team</li>
</ul><div><div><div><p>The annual compensation range for this role is listed below. </p>
<p>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.</p></div><div>Annual Salary:</div><div><span>$405,000</span><span>—</span><span>$485,000 USD</span></div></div></div><div><h2><strong>Logistics</strong></h2>
<p><strong>Minimum education: </strong>Bachelor’s degree or an equivalent combination of education, training, and/or experience</p>
<p><strong>Required field of study: </strong>A field relevant to the role as demonstrated through coursework, training, or professional experience</p>
<p><strong>Minimum years of experience: </strong>Years of experience required will correlate with the internal job level requirements for the position</p>
<p><strong>Location-based hybrid policy:</strong> 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.</p>
<p><strong>Visa sponsorship:</strong> 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.</p>
<p><strong>We encourage you to apply even if you do not believe you meet every single qualification.</strong> 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.<br /><br /><strong>Your safety matters to us.</strong> 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 <u><a href="http://anthropic.com/careers" target="_blank" rel="noopener noreferrer ugc">anthropic.com/careers</a></u> directly for confirmed position openings.</p>
<h2><strong>How we're different</strong></h2>
<p>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.</p>
<p>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 &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.</p>
<h2><strong>Come work with us!</strong></h2>
<p>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. <strong>Guidance on Candidates' AI Usage:</strong> Learn about <a href="https://www.anthropic.com/candidate-ai-guidance" target="_blank" rel="noopener noreferrer ugc">our policy</a> for using AI in our application process.</p></div>

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