Product Manager, Agent Harness (Robotics)

Menlo • Palo Alto, CA

10d

About The Position

Menlo Research is an applied R&D lab building Asimov, an open-source humanoid robot platform, and the software stack that powers it. Its work spans hardware architecture, locomotion, autonomy, simulation, and infrastructure, with a mission to make humanoid labor economically viable.

The Product Manager, Agent Harness will own Menlo’s robotics agent platform, which researches engineering solutions, supports the design of manufacturable robots, trains robots in simulation to perform physical tasks, and helps deploy them in the real world. The role turns the platform’s vision into focused releases, working directly with technical users, researchers, and engineers. The product manager will define agent behavior and workflows, prototype and investigate issues hands-on, and improve reliability using evaluations, user feedback, and telemetry. The role also requires rapidly developing robotics knowledge and working with Brain, Hardware, and Platform specialists to make informed product decisions.

Requirements

• Has built coding agents as a product manager, engineer, or technical founder, with meaningful ownership of shipped capabilities; examples include Codex, Claude Code, Cursor, Devin, Lovable, or comparable agents.
• Understands agent systems deeply and can explain design decisions and tradeoffs involving planning, tool use, context and state management, execution environments, verification, and recovery during long-running tasks.
• Can navigate unfamiliar codebases, prototype agent workflows, integrate tools, and independently investigate failures through code and execution traces.
• Has improved agent reliability measurably using evaluations, user feedback, and telemetry to improve task completion, reduce human intervention, and manage latency and compute.
• Has strong product judgment for autonomous workflows, including how users delegate complex work, inspect results, intervene, and recover from errors.
• Learns unfamiliar technical domains quickly through papers, code, experiments, and collaboration with specialists, and is prepared to develop robotics knowledge for product decisions.
• Works directly with technical users and turns ambitious ideas into focused releases with measurable acceptance criteria.

Nice To Haves

• Familiarity with robotics and physical AI, such as inverse kinematics, motion planning, control, reinforcement learning, imitation learning, vision-language-action models, or world-action models.
• Experience with room scanning, 3D reconstruction, scene understanding, or converting real environments into simulation assets.
• Experience with simulation and robot-learning infrastructure, including training pipelines, reproducible experiments, skill composition, and validation on physical robots.
• Familiarity with robot design and manufacturability, including CAD, component selection, bills of materials, assembly, sourcing, and cost constraints.

Responsibilities

• Own the agent harness end to end, translating its vision into focused releases with measurable acceptance criteria across research and engineering.
• Define how the agent plans, uses tools, manages context and state, executes and verifies work, and recovers during long-running engineering and robotics tasks.
• Shape how users delegate complex physical-world work to the agent, inspect results, intervene, and recover from errors; translate those needs into clear product behavior and a strong developer experience.
• Work directly with technical users to identify initial valuable use cases across engineering research, robot design, simulation training, and deployment.
• Improve agent reliability using evaluations, user feedback, and telemetry to raise task completion, reduce human intervention, and manage latency and compute.
• Prototype agent workflows, integrate tools, and investigate failures through code and execution traces.
• Develop robotics fluency and collaborate with Brain, Hardware, and Platform specialists to make informed product decisions.
• Turn ambitious ideas into focused releases with measurable acceptance criteria while owning outcomes.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed