Work Setup: Hybrid (3 days onsite/week)
Office Location Options:
- Louisville, KY
- Chicago, IL
- New York, NY
- Dallas, TX
- Boston, MA
- Washington, DC
Description
As Humana continues its transformation into an AI-first enterprise, we are looking for a hands-on Senior Product Manager to design, prototype, and scale AI solutions across our business. You will work with cross-functional teams of engineers, designers, data scientists, and business stakeholders to build AI-powered solutions that solve real enterprise problems. You will own an AI product or major capability within our AI portfolio, define what success looks like, build and develop with the team, and drive it from deeply understanding a business challenge, to prototyping an AI solution, to proving its value, to delivering it through Humana's enterprise AI governance process.
What you will own
- Product ownership: Own the discovery, definition, and delivery of an AI product or capability. Write the PRD, define the target-state (north-star) vision, and drive it from concept through prototyping, evaluation, and launch.
- Business discovery: Work directly with business partners to understand their operations, map the service end to end, and turn real problems into scoped AI use cases with a clear value proposition.
- Hands-on prototyping: Build working prototypes and demos yourself with AI tools (for example, Claude Code, Cursor, OpenAI Codex) to test feasibility and value.
- Requirements and scoping: Turn validated use cases into clear, buildable requirements, user stories, acceptance criteria, edge cases, and success metrics, so engineers, data scientists, and designers know exactly what "done" and "good" mean. Shape the end-to-end user experience with design, since enterprise adoption lives or dies on usability.
- Delivery and execution: Drive the build from prototype to production and own the backlog, sequence the work, make scope and tradeoff calls as models and constraints shift, unblock the team, and keep momentum from first demo through launch and iteration.
- Evaluation and quality: Build golden sets and ground truth, run offline and live evals, choose appropriate metrics (accuracy, precision, recall, F1, task success, hallucination rate), and use results, including LLM-as-judge where validated, to decide what ships and to measure impact.
- Solution architecture: Support high-level architecture and feasibility discussions with engineering, while owning the required prompt engineering and/or skill creation components of the AI harness.
- Cross-functional delivery: Partner with engineers, data scientists, and designers to deliver against roadmap and milestones, and contribute to shared playbooks, skills, and patterns.
- Governed delivery: Prepare the documentation, scorecards, and technical detail needed to move your solution through Humana's enterprise AI governance (AIRB, LRC, Responsible AI Council).
- Communication: Communicate progress, requirements, trade-offs, ROI, and eval results clearly to business and technical stakeholders.
- Use your skills to make an impact
Required Qualifications
- B.S. or M.S. in Computer Science, Engineering, or a related field (or equivalent experience)
- 5+ years of product or related experience, including 3+ years in product management, with hands-on experience building or shipping AI/ML or GenAI products.
- You use AI tools regularly and prototype your own ideas.
- Evaluation experience: You have built or run evals, including golden sets, ground truth, and accuracy-, precision-, and recall-based metrics, and used them to make product decisions.
- AI knowledge: A working understanding of modern AI/ML and GenAI: LLMs, RAG, agents, prompt/harness engineering, and evaluation methodology.
- Communication across domains: The ability to move between business and technical language and to build a value proposition and a basic business case.
Preferred Qualifications
- Experience in healthcare, insurance, or another regulated industry.
- Hands-on experience with agent frameworks, GraphRAG / knowledge graphs, or reusable skills / plugins.
- Working proficiency in Python
- Familiarity with responsible AI, bias mitigation, and compliance for sensitive data.
- Comfort with ambiguity and a fast pace, with strong prioritization and problem-solving.