Humana

Sells Medicare health plans and runs senior clinics

Principal Product Manager - AI

Technical Product ManagementUpdated on Nov 12

Full-timeHybrid

About the Job

Requirements

At least 10 years of product or related experience, with AI, machine learning, or generative AI products shipped to production; candidates with fewer years may be considered if they have a strong engineering background and real fluency in AI.
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.
Regularly use AI tools, prototype ideas, and articulate specific desired changes to model behavior and why; understand trade-offs involving context windows, latency, cost, hallucination, and retrieval-augmented generation versus fine-tuning.
Have built evaluations using golden sets, ground truth, and offline and live evaluations; use precision- and recall-based metrics to make product decisions; and have set evaluation standards adopted by other teams.
Apply systems thinking by building reusable infrastructure that prevents recurring classes of problems across the organization.
Move fluently between business and technical concepts, with a track record of business cases, return-on-investment models, and roadmaps that inform executive-level investment decisions.
Have a 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 application to enterprise problems.
Work from first principles, prioritize well, 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 competing product areas, adapt the portfolio as models and business needs change, set the north star and long-term roadmap, and reason from first principles when problems and strategies are undefined.
Partner with business-unit and enterprise leaders to map operations end to end, turn ambiguous high-stakes problems into AI use cases with clear business cases, and sequence those use cases into a portfolio.
Build working prototypes and demonstrations with agentic coding tools such as Claude Code, Cursor, and OpenAI Codex to prove feasibility and value before committing a full team; stay close 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 to support adoption.
Drive the build from prototype to production across the portfolio; sequence work, make scope and trade-off decisions as models and constraints shift, unblock teams, and maintain momentum from initial demonstration through launch and iteration.
Define quality measurement; build golden sets, error budgets, and evaluation frameworks; run offline and production evaluations; select metrics such as precision, recall, task success, and hallucination rate; apply large-language-model-as-judge methods when validated; and use results to make launch decisions and prepare leadership readouts.
Partner with engineering on high-level architecture and feasibility across the portfolio; own context engineering and skill creation in 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; and author playbooks, skills, and solution patterns for building AI.
Move solutions through enterprise AI governance processes, including AIRB, LRC, and the Responsible AI Council; own product documentation, scorecards, and stage-gate reviews; and help shape governance standards as the portfolio grows.
Mentor senior and lead product managers, contribute to hiring and promotion assessments, and set the craft standard for building with AI across the organization.
Communicate strategy, roadmaps, requirements, return on investment, and evaluation results to executive, business, and technical audiences; represent the organization's AI product work with external partners, vendors, and the broader community.
Track advances in models, agents, evaluations, and emerging techniques such as agent harness, loop, and graph or GraphRAG approaches; form a defensible view of their direction and apply them across the portfolio.

Desired Qualifications

At least 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.

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. Prioritize 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.Sequence 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 grows.

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 emerging techniques (agent harness, loop, and graph / GraphRAG approaches), form a defensible point of view on where they are headed, and apply them across your portfolio.

Use your skills to make an impact

Required Qualifications

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.
Portfolio-level impact: A track record of setting strategy and driving delivery across multiple products or a major domain, and of 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, and 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, with a track record of business cases, ROI models, and roadmaps that inform investment decisions at the executive level.
AI knowledge: A deep working understanding of modern AI/ML and GenAI (LLMs, agents, RAG, prompt/harness engineering, and Evals) and how it applies to enterprise problems.
You work from first principles, prioritize well, and make good calls quickly with incomplete information.

Preferred Qualifications

12+ years of product experience, or 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, or an equivalent combination of experience.

Additional Information

Responsible AI

Everything you ship will meet Humana's Responsible AI standards and clear our AI governance stage gates, with safety, fairness, privacy, and compliance built in from the start. As a Principal, you will help set those standards.

Work Style: This position follows a hybrid work schedule, requiring employees to work three days per week in the office and the remaining days remotely. Qualified candidates must currently reside within, or be willing to relocate to, a commutable distance from one of the talent markets listed below.

Office Location Options:

New York, NY
Louisville, KY
Chicago, IL
Dallas, TX

#enterpriseAI

Scheduled Weekly Hours

Pay Range

The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc.$201,600 - $277,200 per yearThis job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance.

Description of Benefits

Humana, Inc. and its affiliated subsidiaries (collectively, “Humana”) offers competitive benefits that support whole-person well-being. Associate benefits are designed to encourage personal wellness and smart healthcare decisions for you and your family while also knowing your life extends outside of work. Among our benefits, Humana provides medical, dental and vision benefits, 401(k) retirement savings plan, time off (including paid time off, company and personal holidays, paid parental and caregiver leave), short-term and long-term disability, life insurance and many other opportunities.

About Us

About Humana: Humana Inc. (NYSE: HUM) is a leading U.S. healthcare company. Through our Humana insurance services and our CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health – delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare and Medicaid, families, individuals, military service personnel, and communities at large. Learn more about what we offer at Humana.com and at CenterWell.com.

Equal Opportunity Employer

It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.

About the Company

Humana

Sells Medicare health plans and runs senior clinics

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, KY
Founded: 1961

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