Product Manager, Agents & Auto-Research

Bedrock is moving AI out of the lab and onto real job sites, retrofitting heavy equipment contractors already own, starting with excavators. The product manager will own the agent platform, where agents run, get evaluated, earn trust for load-bearing work, and get measured, and robotics auto-research, agent loops that improve the autonomy stack, data, simulation and infrastructure. The role reports to the Head of Product and works daily with agent platform, ML, simulation and autonomy engineers.

Responsibilities

Set the strategy and roadmap for agents and auto-research at Bedrock; Define what it takes for an agent to be load-bearing, including evals, reliability bar, human oversight and feedback loop; Turn auto-research from a few promising loops into a production system with budgets, verdicts, provenance and a clear line from experiment to shipped capability; Own metrics such as agent adoption, share of capability work done by auto-research, and cost and time per result; Make internal systems agent-ready so agents can read, act and be held accountable across data, simulation, code, planning and decisions; Keep the company model-agnostic while context, traces and memory stay proprietary; Build and prototype agents, evals and workflows with AI coding tools; Help drive adoption across engineering, operations and commercial teams and know when an agent should not be trusted

Requirements

5+ years in product, research or engineering roles, including shipping LLM agents or AI systems that people rely on in production; Hands-on depth in how frontier models and agents behave: harnesses, tool use, context, evals, cost and failure modes; Experience designing evaluations for open-ended model behavior and making product calls from them; AI-native in your own work, using Claude Code, Codex or similar every day, reading code fluently and shipping prototypes; Comfort with ML experimentation and research workflows, able to follow research discussions with engineers and push on their rigor; Clear, concise writing that turns ambiguous direction into plans with measurable outcomes; A track record of agency, having taken a problem nobody owned and carried it to a real result

Nice to have

Experience at a frontier AI lab or AI-native startup working on agents, evals, RL environments or automated research; Background in robotics, autonomy, simulation or ML infrastructure; Built an internal developer or research platform adopted across many teams; Published research or open-source work on agents, evals or AI for science