Staff Software Engineer, Developer Productivity (Dev Environments) - Claude Code
소프트웨어 엔지니어정규직리드 · 7~10년
Anthropic에서 개발 생산성(Developer Productivity) 팀을 이끌 Staff 엔지니어를 찾습니다. Python 및 컨테이너/Kubernetes 환경에 대한 깊은 이해가 필수이며, Claude 개발 환경의 내부 루프(inner loop) 최적화와 격리 모델 설계를 주도합니다. AI 코딩 도구 활용 경험이 중요하며, 대규모 엔지니어링 조직의 인프라를 개선할 수 있는 기술적 리더십을 갖춘 분을 환영합니다.
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.
Every minute an Anthropic engineer or researcher spends waiting on a container to boot, a dependency to resolve, or CI to surface a failure that could have been caught locally is a minute not spent on frontier AI safety. The Developer Productivity team owns the inner development loop for the people building Claude — and increasingly, for Claude itself as an engineering collaborator.
We're looking for a Staff Software Engineer to own our development environment end to end. You'll make spinning up a fresh environment fast, design the isolation boundary that keeps local experimentation safely separated from shared research and production infrastructure, and build the pre-push validation layer that catches problems before they ever reach CI. You'll also help shape how our repository and platform topology evolves as the company scales, partnering closely with the infrastructure teams who own the substrate you build on.
This team works the way it expects the rest of Anthropic to work: with Claude in the loop. Agentic coding is both how we operate day to day and a core part of what these environments need to support, so we're looking for someone who already builds this way and has informed opinions about where the leverage actually is.
Own the local and hosted development environment end to end — container lifecycle, dependency provisioning, hot reload, and the single command an engineer runs to start working
Drive down cold-start time for fresh development environments and keep it low as the codebase grows
Design and implement the environment isolation model (sandboxes, ephemeral environments, namespace separation) that lets engineers experiment freely without risk to shared systems
Build and maintain the pre-push validation surface so failures are caught on the engineer's machine, not in CI
Partner with platform, delivery infrastructure, and tooling teams to shape the repository and service topology that best supports a fast inner loop
Act as a technical lead across team boundaries — gathering requirements, building consensus, and advocating for the approach that's right for engineers across Anthropic
Significant professional software engineering experience in backend or developer infrastructure domains
Proficiency in Python
Hands-on experience with containers (Docker or equivalent), Kubernetes, and pod-level operations
Prior ownership of a developer environment, build system, or paved-path workflow used by a multi-team engineering organization, with demonstrable adoption
Experience working across team boundaries to deliver infrastructure that other engineers depend on
Daily, hands-on use of AI coding assistants as part of your own development workflow
7+ years of backend or developer infrastructure engineering experience
Experience with Rust or Go
A track record of reducing cold-start or boot time on a complex multi-service stack to under a minute, with before/after measurements
Prior design of environment isolation models such as ephemeral environments, sandboxes, or isolated namespaces
Experience leading (or making the case against) a monorepo extraction, repo split, or comparable scope-boundary migration from the developer-tooling side
Familiarity with Bazel, Buck, Nix, or similar hermetic build systems
Experience operating as a platform tech lead — broad context across the stack and a history of cross-team influence
Rebuilding the dev container image pipeline so a new engineer goes from git clone to a running environment in under 60 seconds
Designing an ephemeral environment system that gives every branch its own isolated copy of downstream services
Shipping a pre-push hook framework that runs the relevant subset of tests and lints locally, cutting CI failure rate for first-attempt pushes
Instrumenting the inner loop to produce a live dashboard of p50/p95 edit-build-test latency across the engineering org
Authoring the design doc and migration plan for how development environments should evolve alongside a major repository restructure
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
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.
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.
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.