Why This Role
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. 

About the Team 
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. 

 
What You’ll Do 

• 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.

• IdentifyAI 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 deeplytechnical concepts into compelling briefings for VP and executive audiences.

• 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 thedeveloperinner loop (IDE, build, test) and outer loop (CI, code review, release).

• AI product experience:you’vemanaged 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.

What Will Give You a Competitive Edge (Preferred Qualifications) 

• 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. 

Hybrid: This role is categorized as hybrid. The successful candidate is expected to report to GMs office in Mountain View, CA or the office in Warren, MI as needed.