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Staff+ Software Engineer, Research Systems Engineering

anthropicRemote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NYPosted 7 Oct 2026

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About this role

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 Infrastructure organization builds and operates the distributed systems that train, serve, and secure our AI models.

Every other team at Anthropic depends on these systems. In this role, you'll work directly with our Research teams to build the reliable, scalable, performant infrastructure our research depends on. This is a cross-functional systems team: you'll scope and lead complex, multi-month infrastructure projects and resolve the performance and scalability bottlenecks that limit how fast we can grow. Key responsibilities Independently scope and lead complex, multi-month infrastructure projects, from an ambiguous starting point through to a production system Build deep partnerships with researchers and Research teams to understand their needs and deliver for them Mentor other engineers and help raise the technical bar for the team Build alignment on technical direction across multiple teams, working through ambiguous problem spaces Take ownership of the reliability, scalability, and security of the systems you build as usage and complexity grow Lead the improvement of operational processes across Infrastructure, such as incident response, postmortems, and on-call rotations, so the team learns from every incident Minimum qualifications Experience designing, building, and operating large-scale distributed systems or infrastructure in production Experience independently scoping and delivering complex, ambiguous, multi-month technical projects Prior experience as a technical lead or mentor for other engineers Experience making architectural decisions that other engineers and teams build on top of Strong software engineering fundamentals and proficiency in at least one programming language (e.g., Python, Rust, Go, Java) Experience with modern cloud infrastructure (e.g., Kubernetes, infrastructure as code, AWS, GCP) Strong written and verbal communication skills, with experience building alignment across multiple teams or stakeholders Preferred qualifications 10+ years of software engineering experience, not including internships Experience with machine learning infrastructure (e.g., GPUs, TPUs, Trainium) and associated networking infrastructure (e.g., NCCL) Low-level systems experience (e.g., Linux kernel tuning, eBPF) Experience applying security or privacy engineering best practices The annual compensation range for this role is listed below.

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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: USD 320,000 — USD 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,

Source listing: greenhouse_anthropic

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