Product Manager – Agents, Auto-Research

Bedrock Robotics

. Set the strategy and roadmap for agents and auto-research at Bedrock .

Posted 11/4/2026full-timeUnited StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and implementing strategies for AI agents and auto-research systems, with a strong focus on metrics, evaluations, and production readiness. Proficient in using AI coding tools and collaborating across engineering and operations teams to drive adoption and innovation.

Highest-signal resume keywords

5+ Years In Product, Research, Or Engineering RolesExperience Shipping LLM Agents Or AI SystemsHands-On Knowledge Of Frontier Models And AgentsDaily Use Of Claude Code, Codex, Or Similar AI Coding ToolsAbility To Evaluate New Models Independently

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Systems DevelopmentModel EvaluationPrototype DevelopmentMetrics MeasurementLoad-Bearing Agent RequirementsReliability ThresholdsHuman OversightFeedback LoopsCost AnalysisSimulation Workflows

Soft Skills

Clear WritingActionable PlanningOwnership Of ProblemsCollaborationCommunication

Tools & Technologies

Claude CodeCodexAI Coding ToolsML Experimentation ToolsSimulation Platforms

Industry Keywords

Frontier AI Lab ExperienceRoboticsAutonomyML InfrastructureAutomated Research

About the role

Key responsibilities & impact

Set the strategy and roadmap for agents and auto-research at Bedrock
Decide which agent and research loops to build based on impact on capability, cost, and speed
Define requirements for load-bearing agents, including evaluations, reliability thresholds, human oversight, and feedback loops
Turn auto-research loops into a production system with budgets, verdicts, provenance, and a path from experiment to shipped capability
Own and measure metrics including agent adoption, capability work completed by auto-research, and cost and time per result
Make internal systems agent-ready across data, simulation, code, planning, and decisions
Maintain model agnosticism while retaining ownership of context, traces, and memory
Prototype agents, evaluations, and workflows using AI coding tools
Drive adoption across engineering, operations, and commercial teams
Determine when an agent should not be trusted
Report to the Head of Product
Work daily with agent platform, ML, simulation, and autonomy engineers

Requirements

What you’ll need

5+ years in product, research, or engineering roles
Experience shipping LLM agents or AI systems relied upon in production
Hands-on knowledge of frontier models and agents, including harnesses, tool use, context, evaluations, cost, and failure modes
Ability to evaluate new models independently within days of release
Experience designing evaluations for open-ended model behavior and making product decisions from them
Daily use of Claude Code, Codex, or similar AI coding tools
Fluency reading code and shipping prototypes
Comfort with ML experimentation and research workflows
Ability to follow research discussions with engineers and assess rigor
Clear, concise writing and ability to turn ambiguity into actionable plans with measurable outcomes
Track record of taking ownership of unowned problems through real results
Preferred: experience at a frontier AI lab or AI-native startup working on agents, evaluations, RL environments, or automated research
Preferred: background in robotics, autonomy, simulation, or ML infrastructure
Preferred: experience building an internal developer or research platform adopted across many teams
Preferred: published research or open-source work on agents, evaluations, or AI for science
Legally authorized to work in the United States (application requirement)
Must answer whether visa sponsorship will be required to work in the United States

Benefits

Comp & perks

Equal Opportunity Employer commitment
Reasonable accommodations during the hiring process
Opportunity to work on meaningful autonomy and robotics problems
Scope to own a frontier product area at a rapidly scaling company