The Developer Productivity team at Anthropic owns the end‑to‑end path from pull request to production, focusing on CI, merge queues, deploy pipelines, and AI‑assisted code review. This staff‑level, tech‑lead role shapes the CI and repository topology for Claude and research infrastructure, drives metrics like "time from push to healthy in prod," builds canary and progressive release mechanisms, improves test reliability, and represents the team in cross‑organization pipeline decisions. The position blends deep backend and developer‑infrastructure expertise with AI tooling and cross‑team collaboration.
Staff Software Engineer, Developer Productivity (CI/CD) - Claude Code en Anthropic
Híbrido - San Francisco, CA, United States
Más vacantes en AnthropicSalary
USD 405,000 - 485,000
Requirements
Skills
- Significant backend or developer-infrastructure engineering experience
- 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 (Go or Rust)
- Experience operating CI/CD or release systems through production incidents, including writing post‑mortems
- Demonstrated ability to work across team boundaries and build consensus
- Comfort using AI coding tools as a daily part of your workflow
- 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)
- Track record of leading or making a well‑reasoned case against repo split, monorepo extraction, or comparable scope‑boundary migration
- History of authoring engineering policy or paved‑path tooling adopted voluntarily by other teams
- Familiarity with Kubernetes, Buildkite, GitHub Actions, or comparable CI/deploy substrates
- Interest in the safe and beneficial development of AI
Responsibilities
- Own the build, test, merge, and deploy pipeline end to end
- 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)
- Improve test reliability by quarantining, root‑causing, and retiring intermittent failures
- Shape CI and repository topology (build graph, test targeting, scope boundaries)
- Partner with platform, delivery infrastructure, and security teams, representing Developer Productivity in cross‑org pipeline decisions
- Design processes (postmortem review, incident response, on‑call) that help the team operate reliably and avoid repeated failures
Technologies
PythonGoRustBazelKubernetesBuildkiteGitHub ActionsCI/CDMerge queueDeploy pipeline
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