PMs for Hire

PMs for Hire

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

San Francisco, CA · Staff+

H1B sponsorship available$405k-$485kDetected 27 days ago
PythonGoRustCode ReviewGitKubernetesCI/CDGitHub ActionsNLPIncident ResponseLogisticsResearchCommunication

About the role

  • Every engineer at Anthropic depends on the path from pull request to production.
  • 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.

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
  • 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
  • Demonstrated ability to work across team boundaries - building consensus with platform, security, and product engineering stakeholders

Requirements

  • 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
  • Years of experience required will correlate with the internal job level requirements for the position

Nice to have

  • 7+ years of backend or developer-infrastructure experience
  • Experience with Bazel or similar build-graph / test-targeting systems at monorepo scale
  • 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
  • Reducing p50 merge-to-production time by re-architecting the merge queue and test selection strategy
  • Designing a flaky-test quarantine and burndown system that returned CI signal to >99% reliability

Compensation

  • $405,000 - $485,000 USD
  • 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
  • However, some roles may require more time in our offices.

Benefits

  • Build the deploy and release path - canary, progressive rollout, health checks, automated rollback - in partnership with the platform teams who own the underlying substrate
  • Minimum education: Bachelor's degree or an equivalent combination of education, training, and/or experience

Company info

  • Comfort using AI coding tools as a daily part of your workflow, with informed opinions on where they provide leverage

Visa & Work Authorization

  • 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 do sponsor visas!

This listing is sourced directly from PMs for Hire's careers page and normalized into a canonical job model.