Product Manager, Developer Productivity

About the role

As a Product Manager focused on Developer Productivity, you'll partner with Infrastructure, Inference, Research, and Product Engineering to build the systems that determine how thousands of engineers and researchers at Anthropic develop, build, test, and ship code—the foundation on which every model, evaluation, and product feature depends:

• Partner with Developer Productivity engineering teams to own the end-to-end developer experience—from the source control and language ecosystems that underpin our monorepo, to the build and CI infrastructure that keeps thousands of daily builds running reliably across multiple cloud providers, to the acceleration tooling that deeply integrates Claude into every engineer's workflow.
• Your work directly impacts engineering velocity across the entire company: defining the abstractions for how code moves from idea to production, establishing the metrics that surface friction before it compounds, and making the trade-offs that keep a rapidly scaling engineering organization shipping with confidence.
• You'll drive the evolution of our developer platform through a fundamental shift in how software gets built—as AI agents move from autocomplete to autonomous collaborators, the definition of "developer" is changing, and our tooling, governance, and workflows must change with it. You'll be defining what developer productivity means when a meaningful share of code is written, tested, and reviewed by Claude itself.
• You will define and own the strategy and roadmap across build systems, CI/CD pipelines, developer environments, accelerator toolchain management (GPU, TPU, Trainium), and the AI-native acceleration layer that makes Anthropic the most productive place in the world to build frontier AI.

Responsibilities:

• Deeply understand the needs of internal customers across Research, Inference, Infrastructure, and Product—from researchers iterating on training code who need fast, reproducible builds to inference engineers managing compute-intensive toolchains with strict compatibility constraints.
• Define and iterate on the developer experience model: the workflows, tooling primitives, and feedback loops that govern how engineers and AI agents collaborate on code—including how we measure productivity when the unit of work is no longer a human typing.
• Partner with engineering leads to design build, CI, and test infrastructure that scales non-linearly with engineering headcount—ensuring that as Claude takes on more of the inner loop, the outer loop (review, validation, deployment) doesn't become the new bottleneck.
• Drive product strategy and roadmap for developer acceleration, including AI-assisted code review, agent-driven test generation, automated dependency management, and the governance frameworks that let teams safely delegate work to autonomous systems.
• Own the trade-off framework between velocity, reliability, security, and cost—making transparent prioritization decisions about where to invest in human workflows versus agent workflows, and communicating them clearly to senior leadership.
• Establish and champion the productivity metrics that matter in an AI-native engineering org—moving beyond commits and cycle time to measures that capture human-agent collaboration effectiveness, toil eliminated, and time-to-confident-ship.
• Build conviction about where developer tooling is headed on a 2–3 year horizon, and translate that into a r…