Staff Software Engineer, Developer Productivity (CI/CD) - Claude Code

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 Every engineer at Anthropic depends on the path from pull request to production. The Developer Productivity team owns that path end to end — review automation, CI, the merge queue, the deploy pipeline, and the policy that gates each step. These pieces exist today; the opportunity is to integrate them into a single fast, predictable system that scales with the volume of code shipping into Claude and our research infrastructure.   In this role, you'll be responsible for making "time from push to healthy in production" a metric the whole company can rely on. You'll shape the CI and repository topology that best serves our velocity, build AI-assisted review that keeps confidence high as PR volume grows, and partner closely with platform, security, and delivery infrastructure teams on the substrate underneath. This is a tech-lead-scope IC role with broad cross-team influence — you'll represent Developer Productivity in org-wide pipeline decisions and help other teams adopt the standards you set.   We use Claude heavily in our own development workflows, and this team is at the center of that: agentic coding is both how we work and part of what you'll be building. Key responsibilities Own the build, test, merge, and deploy pipeline end to end — what runs on each PR, what auto-approves, what gates merge, and how a change progresses to running healthy in production Drive down and defend "time from push to healthy in prod" as a core engineering metric Design and tune AI-assisted code review so confidence-to-land scales with PR volume Build the deploy and release path — canary, progressive rollout, health checks, automated rollback — in partnership with the platform teams who own the underlying substrate Improve test reliability by quarantining, root-causing, and retiring intermittent failures Shape CI and repository topology (build graph, test targeting, scope boundaries) to match how the company actually ships Partner with platform, delivery infrastructure, and security teams, and represent Developer Productivity in cross-org pipeline decisions Design processes (postmortem review, incident response, on-call) that help the team operate reliably and never fail the same way twice Minimum qualifications Significant backend or developer-infrastructure engineering experience, with hands-on responsibility for a high-leverage CI/CD, merge queue, or land pipeline at scale Proficiency in Python and at least one statically-typed systems language (e.g., Go or Rust) Experience operating CI/CD or release systems through production incidents, including writing postmortems and driving remediations Demonstrated ability to work across team boundaries — building consensus with platform, security, and product engineering stakeholders Comfort using AI coding tools as a daily part of your workflow, with informed opinions on where they provide leverage Preferred qualifications 7+ years of backend or developer-infrastructure experience Experience with Bazel or similar build-graph / test-targeting systems at monorepo scale Experience with progressive delivery or release engineering at scale (canary analysis, automated rollback, health-gated promotion) A track record of leading — or making the well-reasoned case against — a repo split, monorepo extraction, or comparable scope-boundary migration A history of authoring engineering policy or paved-path tooling that other teams adopted voluntarily Familiarity with Kubernetes, Buildkite, GitHub Actions, or comparable CI/deploy substrates Interest in the safe and beneficial development of AI Representative projects Reducing p50 merge-to-production time by re-architecting the merge queue and test selection strategy Building an AI-assisted review layer that auto-approves low-risk changes and routes high-risk ones to the right reviewers Designing a flaky-test quarantine and burndown system that returned CI signal to >99% reliability Standing up canary and progressive rollout for a service fleet, with automated rollback on health regression Authoring the RFC and migration plan for a build-graph or repository topology change adopted across multiple teams 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 combinati