Product Manager, Developer Productivity

Details

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. The team includes researchers, engineers, policy experts, and business leaders working to build beneficial AI systems.

Role overview

As a Product Manager focused on Developer Productivity, you will partner with Infrastructure, Inference, Research, and Product Engineering to build systems that determine how engineers and researchers develop, build, test, and ship code. The role covers ownership of the end-to-end developer experience across source control and language ecosystems for a monorepo, build and CI infrastructure spanning multiple cloud providers, and acceleration tooling that integrates Claude into engineers' workflows. You will define abstractions for how code moves from idea to production, establish metrics to surface friction, and make trade-offs to keep a rapidly scaling engineering organization shipping with confidence. You will also drive the evolution of the developer platform as AI agents shift developers' workflows from autocomplete toward autonomous collaborators.

Responsibilities

• Partner with Developer Productivity engineering teams to own the end-to-end developer experience—from source control and language ecosystems for the monorepo to build and CI infrastructure and acceleration tooling integrated with Claude.
• Define the developer experience model: workflows, tooling primitives, and feedback loops for human-agent collaboration on code, and define how productivity is measured when agents contribute to code.
• Design scalable build, CI, and test infrastructure with engineering leads so infrastructure scales non-linearly with headcount and avoids new bottlenecks as agents take on more of the inner loop.
• Drive product strategy and roadmap for developer acceleration: AI-assisted code review, agent-driven test generation, automated dependency management, and governance frameworks for delegating work to autonomous systems.
• Own trade-offs between velocity, reliability, security, and cost; prioritize investments in human workflows vs. agent workflows and communicate decisions to senior leadership.
• Establish and champion productivity metrics for an AI-native engineering org (beyond commits and cycle time), including human-agent collaboration effectiveness, toil eliminated, and time-to-confident-ship.
• Build a 2–3 year conviction on where developer tooling is headed and translate that into a forward-looking roadmap.

Requirements

• 7+ years of product management experience, with deep exposure to developer tooling, build systems, CI/CD, or platform infrastructure.
• Experience taking technical platform products from infancy to scale and growing them to serve demanding internal or external engineering customers.
• Track record building platform products that balance multiple engineering personas and making prioritization trade-offs between velocity, reliability, and security.
• Ability to internalize complex technical systems (build systems, monorepos, CI pipelines, accelerator toolchains) and translate that understanding into a product vision.
• Credibility across functions: able to discuss build graph optimization with engineers, developer velocity economics with leadership, and AI-agent governance with security teams.
• A strong thesis on how AI will reshape software development and enthusiasm for defining tooling when agents write, review, and ship significant portions of code.
• Scrappy and resourceful: able to move quickly in a fast-paced environment.

Strong candidates may have

• Built or scaled developer productivity, build systems, or CI/CD platforms for large engineering organizations (examples: Bazel, Buck, large-scale monorepos, or custom build infrastructure).
• Experience defining and operationalizing engineering productivity metrics (DORA, SPACE, or custom frameworks) and a point of view on how these evolve with AI agents in the loop.
• Familiarity with accelerator toolchain ecosystems (CUDA/GPU, TPU, AWS Neuron/Trainium) and developer experience challenges for compute-intensive ML workloads.
• Experience shipping AI-native developer tooling (code assistants, agent-based automation, AI-integrated IDEs) and understanding governance, trust, and adoption challenges.
• Experience scaling through hypergrowth in engineering-intensive environments (AI/ML, large-scale cloud infrastructure, or developer tools companies) and driving internal platform adoption.

Compensation

Annual Salary: $385,000 - $595,000 USD

Logistics

• Minimum education: Bachelor’s degree or equivalent combination of education, training, and/or experience.
• Minimum years of experience: Correlates with internal job level requirements.
• Location-based hybrid policy: staff are expected to be in one of Anthropic's offices at least 25% of the time; some roles may require more office time.
• Visa sponsorship: Anthropic states they do sponsor visas and retain an immigration lawyer to assist, though sponsorship is not guaranteed for every role/candidate.

How we're different

Anthropic focuses on large-scale research efforts as a cohesive team and values impact and communication. The posting references recent research directions related to GPT-3, interpretability, scaling laws, AI & compute, and learning from human preferences.

Additional notes

The role emphasizes collaboration with Research, Inference, Infrastructure, and Product Engineering and a focus on defining developer productivity and tooling in an AI-native engineering environment.