Principal Product Manager, AI
$201,600–$277,200 year
HybridChicago, Illinois, United States or New York City, New York, United States
Job Summary
Define the multi-year vision and strategy for a portfolio of AI products, prioritizing across competing areas and adapting to shifting model landscapes. Partner with enterprise leaders to map operations, turning ambiguous problems into a sequenced slate of AI use cases with clear business cases. Build working prototypes using agentic coding tools to prove feasibility before full team commitment, then drive delivery from prototype to production while making scope and tradeoff calls. Define quality standards through golden sets, error budgets, and eval frameworks, running offline and production evaluations to inform launch decisions. Lead engineers, data scientists, designers, and business partners through influence, authoring playbooks and solution patterns for the organization. Move solutions through enterprise AI governance, setting standards for safety, fairness, and compliance. Mentor senior product managers and contribute to hiring assessments to raise the craft standard across the team.
Required Qualifications
- 10+ years of product or related experience
- AI/ML or GenAI products shipped to production
- Portfolio-level impact: A track record of setting strategy and driving delivery across multiple products or a major domain
- Leading initiatives with org-wide, executive-level visibility
- Hands-on building: You use AI tools regularly, prototype your own ideas, and can say specifically what you would change about a model's behavior and why
- You know the trade-offs that matter: context windows, latency, cost, hallucination, and RAG versus fine-tuning
- Evaluation expertise: You have built evals (golden sets, ground truth, and offline and live evals) and used precision- and recall-based metrics to make product decisions
- You have set eval standards that other teams adopt
- Systems thinking: When you find a problem, you build the infrastructure that prevents the whole class of problem, and you make that infrastructure reusable across the organization
- Communication across domains: You move fluently between business and technical concepts
- A track record of business cases, ROI models, and roadmaps that inform investment decisions at the executive level
- A deep working understanding of modern AI/ML and GenAI (LLMs, agents, RAG, prompt/harness engineering, and Evals)
- How it applies to enterprise problems
- You work from first principles
- Prioritize well
- Make good calls quickly with incomplete information
- Work three days per week in the office and the remaining days remotely
- Currently reside within, or be willing to relocate to, a commutable distance from one of the talent markets listed below
Desired Qualifications
- 12+ years of product experience
- An equivalent depth of AI-native building, in a large enterprise environment
- Experience in healthcare, insurance, or another regulated industry
- A well-supported, publicly demonstrated point of view on where agentic AI, evals, and AI-native product development are headed
- Hands-on experience with agent frameworks, GraphRAG / knowledge graphs, and reusable skills / plugins
- Experience defining a new AI product category or standing up cross-organization AI standards and playbooks
- Familiarity with responsible AI, bias mitigation, and compliance with sensitive data
- A degree in computer science or engineering
- An equivalent combination of experience
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