Principal Product Manager - AI
$201.6k - $277.2k/yr+ Bonus incentive plan
Expert
Bachelor's
New York, NY, USA
HybridThree days per week in the office; candidates must reside within or relocate to commuting distance of New York, NY.
ProductTechnical Product Management
About the job
Requirements
- 10+ years of product or related experience, with AI/ML or GenAI products shipped to production; candidates with fewer years but a strong engineering background and real fluency in AI will be considered.
- A track record of setting strategy and driving delivery across multiple products or a major domain, and of leading initiatives with organization-wide, executive-level visibility.
- Regular use of AI tools and ability to prototype ideas, specify changes to model behavior and explain why, and assess trade-offs involving context windows, latency, cost, hallucination, and retrieval-augmented generation versus fine-tuning.
- Experience building evaluations, including golden sets, ground truth, and offline and live evaluations; using precision- and recall-based metrics for product decisions; and setting evaluation standards adopted by other teams.
- Systems thinking, including building reusable infrastructure to prevent classes of problems across the organization.
- Ability to communicate across business and technical domains, with a track record of business cases, return-on-investment models, and roadmaps that inform executive-level investment decisions.
- Deep working understanding of modern artificial intelligence, machine learning, and generative AI, including large language models, agents, retrieval-augmented generation, prompt and harness engineering, and evaluations, and their enterprise applications.
- Ability to work from first principles, prioritize, and make sound decisions quickly with incomplete information.
Responsibilities
- Define the multi-year vision and strategy for a portfolio of AI products and capabilities, prioritize across product areas, adapt the portfolio as models and business needs change, set the long-term roadmap, and reason from first principles when problems and opportunities are not yet defined.
- Partner with business-unit and enterprise leaders to map operations end to end, turn high-stakes problems into AI use cases with clear business cases, and sequence them into a portfolio.
- Build working prototypes and demos using agentic coding tools such as Claude Code, Cursor, and OpenAI Codex to prove feasibility and value; stay close enough to the technology to make credible technical decisions.
- Turn validated use cases into buildable requirements, including user stories, acceptance criteria, edge cases, and success metrics; shape the end-to-end user experience with design.
- Drive delivery from prototype to production across the portfolio, sequence work, make scope and trade-off decisions as models and constraints change, unblock teams, and sustain progress through launch and iteration.
- Define quality measures; build golden sets, error budgets, and evaluation frameworks; run offline and production evaluations; select metrics such as precision, recall, task success, and hallucination rate; use large-language-model-as-judge methods where validated; and translate results into launch decisions and leadership readouts.
- Partner with engineering on high-level architecture and portfolio feasibility; own the context-engineering and skill-creation components of the AI harness and establish reusable patterns.
- Lead engineers, data scientists, designers, product managers, and business partners without direct authority; influence vice-president-level organizations through written narratives, business cases, and executive forums; author AI playbooks, skills, and solution patterns.
- Move solutions through enterprise AI governance, including AIRB, LRC, and the Responsible AI Council; own product documentation, scorecards, and stage-gate reviews; and help shape governance standards.
- Mentor senior and lead product managers, contribute to hiring and promotion assessments, and set organizational craft standards for building with AI.
- Communicate strategy, roadmap, requirements, return on investment, and evaluation results to executive, business, and technical audiences; represent the company's AI product work externally with partners, vendors, and the broader community.
- Track advances in models, agents, evaluations, and emerging techniques such as agent harness, loop, and graph/RAG approaches; form a defensible point of view and apply emerging techniques across the portfolio.
- Ensure shipped products meet Responsible AI standards and pass governance stage gates, incorporating safety, fairness, privacy, and compliance from the outset.
- Work three days per week in the New York office and the remaining days remotely; reside within, or be willing to relocate to, commuting distance of the office.
Desired Qualifications
- 12+ years of product experience, or 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 the direction of agentic AI, evaluations, and AI-native product development.
- Hands-on experience with agent frameworks, GraphRAG or knowledge graphs, and reusable skills or plugins.
- Experience defining a new AI product category or establishing cross-organization AI standards and playbooks.
- Familiarity with responsible AI, bias mitigation, and compliance involving sensitive data.
- A degree in computer science or engineering, or an equivalent combination of experience.
About the company
Humana sells health insurance paid for by government programs, chiefly Medicare Advantage plans that private insurers run for Americans 65 and older in place of traditional Medicare. It ranks among the largest Medicare Advantage insurers in the country and also runs Medicaid plans for low-income families in several states. Its CenterWell business operates senior primary care clinics, a mail-order pharmacy and home health services, so many members get care from a company the insurer owns. Medicare and states pay Humana a set monthly amount per member, and it keeps the difference between those payments and members' medical costs. Humana was founded in 1961 as a nursing home company and is based in Louisville, Kentucky.
Company Size
10,001+
Company Stage
IPO
Headquarters
Louisville, Kentucky
Founded
1961
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Simplify's Take
What believers are saying
- Enrollment is surging: in July 2026 Humana affirmed about 25% individual Medicare Advantage membership growth for 2026.
- Owned clinics create clinical careers: CenterWell Senior Primary Care added 130,900 patients, up 27%, in early 2026.
- Medicaid is widening: Illinois chose Humana in June 2026 to run Medicaid coverage statewide.
What critics are saying
- Low quality scores cut Medicare bonuses: only 20% of Humana's members sat in 4-star or better plans for 2026.
- The insurer is shrinking to save margins: about 600,000 Medicare Advantage members got plan-closure notices in October 2026.
- Stock grants carry risk: in July 2026 Humana cut its 2026 GAAP earnings floor to $6.52 a share from $8.36.
What makes Humana unique
- Military families are a second market: Humana runs the Pentagon's TRICARE health plan across 24 eastern states and Washington, DC.
- Florida anchors the business: Humana's Medicare Advantage contracts there produced 14% of its 2025 revenue.
- Medicaid is a quiet second insurer: Humana covers over 1.54 million low-income members across 11 states.
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Benefits
- Health Insurance
- Dental Insurance
- Vision Insurance
- Life Insurance
- Disability Insurance
- Unlimited Paid Time Off
- Paid Vacation
- Paid Parental Leave
- Short-term Disability
- Long-term Disability
- 401(k) Retirement Plan
- 401(k) Company Match