AI Product Manager
Summary
Own AI product strategy, define LLM and agentic systems, set guardrails, and lead safety testing for a company building AI-driven solutions.
- Define AI success metrics
- Define LLM and agentic systems in production
- Define conversational and multi agent deployment
- Define tool usage boundaries
- Design multi agent orchestration and task decomposition
- Drive customer discovery and feedback loops
- Ensure agent systems are testable and debuggable
- Improve AI observability
- Lead LLM safety testing
- Make go no-go decisions for AI changes
- Own AI evaluation strategy
- Own AI product strategy
- Partner on grounding strategies and constraints
- Run experiments and analyze results
- Set AI guardrails and quality standards
- Track AI quality metrics task success hallucinations latency
- Translate AI strategy into requirements roadmaps backlogs