Product Manager
Leads the end-to-end product strategy, quality, and roadmap for an AI agent serving millions of users. The role requires 6+ years of software-industry experience, hands-on agent development, technical fluency with evaluations and traces, and strong product judgment.
About the job
Responsibilities
- Represent the user by synthesizing findings on agent performance and behavior and bringing them to the team with clarity and conviction.
- Run discovery end-to-end, including user interviews, competitive research, evaluation analysis, prompt experimentation, and messaging for upcoming agent capabilities.
- Own the quality bar for agent outputs.
- Drive evaluation infrastructure, monitor regressions, and ensure the agent improves with every release.
- Scope functionality ruthlessly: ship the right slice, validate it through user feedback and metrics, and cut what does not work.
- Enable sales, support, and marketing with context to communicate new agent capabilities effectively.
Requirements
- 6+ years in the software industry.
- Direct ownership of an AI- or LLM-powered product in a product management or engineering leadership role.
- Hands-on experience building and shipping agent-based systems.
- Understanding of tool use, planning loops, multi-step reasoning, and agent failure modes.
- Technical fluency, including programming experience and the ability to read model outputs, traces, and evaluations confidently.
- Strong product sense and systems thinking.
- Ability to determine when to move quickly and when to invest in foundational work.
- Strong judgment about agent communication, error recovery, and earning user trust.
Nice-to-haves
- Deep familiarity with prompt engineering and evaluation frameworks.
- Experience operating at the frontier where best practices are still being established.
Initial Projects
- Rebuild the agent evaluation framework to catch regressions before release.
- Run discovery on major gaps in agent reliability and trust.
- Define and ship the first iteration of improved agent error recovery and communication.
Skills
Artificial Intelligence, LLMs, AI Agents, Tool Use, Planning Loops, Prompt Engineering, Evaluation Frameworks, User Interviews, Competitive Research, Product Discovery, Model Outputs, Model Traces, Metrics, Error Recovery, Systems Thinking
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