Principal Product Manager, AI

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About the role

Become a part of our caring community   As Humana continues its transformation into an AI-first enterprise, we are looking for a hands-on, technically deep Principal Product Manager to define strategy and drive delivery across a portfolio of AI products. You will set the standard for how we build AI at Humana, and personally go deep, from understanding a business challenge, to prototyping an AI solution, to proving its value, to delivering it through Humana's enterprise AI governance process. You will lead through influence, making engineers, data scientists, designers, product managers, and business leaders more effective. What you will own   • Portfolio strategy and vision: Define the multi-year vision and strategy for a portfolio of AI products and capabilities. P rioritize across competing product areas and adapt the portfolio as the model landscape and the business change. Set the north-star and the long-term roadmap, and reason from first principles when the problem, opportunity, and strategy are not yet defined.   • Business discovery at scale: Partner with business-unit and enterprise leaders to map their operations end to end. Turn ambiguous, high-stakes problems into a slate of AI use cases, each with a clear business case, and sequence them into a portfolio.   • Hands-on prototyping: Build working prototypes and demos with agentic coding tools (Claude Code, Cursor, OpenAI Codex) to prove feasibility and value before a full team is committed. Stay close enough to the technology to make credible technical calls.   • Requirements and scoping: Turn validated use cases into buildable requirements: user stories, acceptance criteria, edge cases, and success metrics. Shape the end-to-end user experience with design, because adoption depends on usability.   • Delivery and execution: Drive the build from prototype to production across your portfolio . S equence the work, make scope and tradeoff calls as models and constraints shift, unblock teams, and keep momentum from first demo through launch and iteration.   • Evaluation and quality standards: Define how quality is measured. Build golden sets, error budgets, and eval frameworks; run offline and production evals; choose the right metrics (precision, recall, task success, hallucination rate); apply LLM-as-judge where it has been validated . Turn results into launch decisions and leadership readouts.   • Solution architecture: Partner with engineering on high-level architecture and feasibility across the portfolio, while owning the context engineering and skill-creation components of the AI harness and setting the reusable patterns others build on.   • Cross-organizational leadership: Lead engineers, data scientists, designers, product managers, and business partners without direct authority. Influence VP-level organizations through written narratives, business cases, and executive forums. Author the playbooks, skills, and solution patterns for building AI at Humana.   • Governed delivery: Move solutions through Humana's enterprise AI governance (AIRB, LRC, Responsible AI Council), owning the product documentation, scorecards, and stage-gate reviews, and help shape the governance standards themselves as the portfolio grow s.   • Talent and standards: Raise the bar for the whole team. Mentor senior and lead product managers, contribute to hiring and promotion assessments, and set the craft standard for building with AI across the organization.   • Communication and influence: Communicate strategy, roadmap, requirements, ROI, and eval results clearly to executive, business, and technical audiences, and represent Humana's AI product work externally with partners, vendors, and the broader community.   • Staying current: Track advances in models, agents, evals, and emerg

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