Staff Product Manager, AI Developer Productivity

GM•Sunnyvale, CA

21h•Hybrid

About The Position

General Motors pioneers the innovations that move and connect people to what matters. We see a world with zero crashes, zero emissions, and zero congestion. As we move toward this vision, software plays an integral role as it becomes more prominent in our vehicles. Our ambition in Vehicle Autonomy Product Management is to build a world-class software development culture that is part of the company’s shared vision. We are creating an elite portfolio of software-defined vehicles by tightly integrating software, hardware, and services to create complete and compelling vehicle experiences for our customer s. AI is already a vital part of our development process, contributing significantly to our core codebase. Engineers are realizing substantial productivity gains through AI-powered tools. We've proven the value — now it's time to dramatically expand its impact. This role owns the product strategy for that scaling effort. You’ll define how agentic workflows — AI agents that execute multi-step development tasks autonomously — move from advanced-user adoption to mainstream engineering practice. This is a rare intersection: AI developer productivity at production scale, inside a safety-critical autonomous vehicle program. GM’s AV division runs one of the industry’s largest autonomous vehicle fleets. Your work enables the hundreds of engineers building that platform — developer productivity at scale inside a safety-critical program. AV Developer Productivity owns the developer experience across GM’s AV division — build systems, CI/CD pipelines, developer tooling, observability, and our AI productivity platform. You’ll work directly with senior engineering managers and Staff+ ICs across multiple AI productivity teams and a dedicated ADAS convergence Build & Integration team. We invest in best-in-class AI coding tools, integrate internal MCP servers, and have built infrastructure that enables AI agents to run builds and tests at monorepo scale. Day-to-day, you’ll report to AV Product Management and partner closely with the Developer Productivity engineering leadership team. We don’t expect AV domain expertise on day one — we’ll invest in your ramp-up. Success requires strong technical judgment, principled decision-making, and the ability to build alignment across engineering, infrastructure, and vehicle teams. You should be comfortable navigating ambiguity, making tough tradeoffs, and translating business needs into engineering priorities.

Requirements

You’re a product manager with deep developer tools experience who has been tracking the AI coding revolution and wants to own the product strategy at scale.
You’re equally comfortable writing a PRD for an agentic orchestration framework and presenting a convergence business case to a VP.
You’ve shipped products that engineers love, and you know that adoption is as much about community and communication as it is about features.
5+ years of product management in developer tools, developer platforms, or infrastructure — internal or external engineering audiences.
Technical credibility: you engage credibly with Staff-level engineers on build systems, CI/CD, monorepos, and development environments; you understand the developer inner loop (IDE, build, test) and outer loop (CI, code review, release).
AI product experience: you’ve managed or shipped AI-powered developer tools, coding assistants, LLM applications, or agentic workflows (e.g., GitHub Copilot, Cursor, internal LLM tools, or agent orchestration platforms).
Data-driven product sense: you prioritize using telemetry, user research, and developer experience data — comfortable making directional decisions with imperfect information.
Strong communication: clear PRDs, strategy documents, and executive briefings that translate technical depth without losing substance.

Nice To Haves

Experience navigating complex technical transitions — platform migrations, ecosystem mergers, or large-scale organizational change.
Experience with agentic AI workflows, Model Context Protocol (MCP), or AI coding assistants (Cursor, GitHub Copilot, Claude Code).
Background in build/CI infrastructure (Bazel, Buildkite, Remote Build Execution) or developer experience measurement (DX surveys, DORA metrics, productivity dashboards).
Experience in automotive, robotics, embedded systems, or safety-critical software.

Responsibilities

Own the product roadmap covering agentic execution environments, the skills and MCP (Model Context Protocol) ecosystem, agent orchestration, and AI-powered code review; deliver a 12– 18 month plan with clear milestones and success criteria.
Drive developer adoption through training, newsletters, cross-team projects, and developer feedback sessions to move engineers from passive AI use to agentic workflows.
Define and track success metrics
Coordinate across teams as the product voice spanning Agentic Execution, Agentic Primitives, Agent Orchestration, AI Reviews, and the Developer Experience data platform.
Shape vendor strategy: evaluate external AI tooling and ensure internal investments amplify vendor capabilities rather than duplicating them.
Own ADAS ecosystem discovery by mapping tools, workflows, build systems, and day-to-day dependencies that ADAS engineers rely on.
Define migration waves and priorities with the convergence Build & Integration team, including success criteria and risk frameworks for moving ADAS workflows onto the unified platform.
Build the business case for convergence by quantifying dual-ecosystem costs and their impact on engineering velocity.
Identify AI acceleration opportunities where agentic tools can speed up migration — automated build file generation, AI-assisted onboarding, and agent-driven code migration.
Communicate to leadership: translate deeply technical concepts into compelling briefings for VP and executive audiences.