Interested in this AI Product Manager role at Humana?
Apply Now →Skills & Technologies
About This 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 proficient Lead Product Manager to lead the design, prototyping, and scaling of 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 lead and drive a complex product area within our AI portfolio, define what success looks like, build and develop with the team, and drive results across the organization, moving 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
- Strategy and roadmap:Define the vision, strategy, and roadmap for a complex AI product area. Decide what to build and why, prioritize across competing opportunities, and adapt as the model landscape and the business change.
- Business discovery:Partner directly with business units to map their operations end to end (service design), then translate ambiguous business problems into clearly scoped AI use cases with a clear value proposition, business case, and ROI justification.
- Hands\-on prototyping:Build working prototypes and demos yourself using agentic coding and AI tools (for example, Claude Code, Cursor, OpenAI Codex) to test feasibility and value before committing a full team.
- 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:Own how quality is defined and measured. Build golden sets and ground truth, run offline and live (production) evals, choose appropriate metrics (accuracy, precision, recall, F1, task success, hallucination rate), apply LLM\-as\-judge where it has been validated, and turn results into launch decisions and readouts for leadership.
- SupportSolution 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 leadership:Lead engineers, data scientists, designers, and business partners without direct authority. Author reusable playbooks, skills, and solution patterns that make AI delivery faster and more consistent across the organization.
- Governed delivery:Move solutions through Humana's enterprise AI governance (AIRB, LRC, Responsible AI Council), owning the product documentation, scorecards, and stage\-gate reviews.
- Communication and mentorship:Communicate strategy, requirements, roadmap, ROI, and eval results clearly to executive and technical audiences. Mentor product managers and raise the team's standard for building with AI.
- Staying current:Track advances in models, agents, evals, and emerging techniques (agent harness, loop, and graph / GraphRAG approaches) and apply them in your portfolio.
Use your skills to make an impact
=====================================
Required Qualifications
- 7\+ years of product or related experience, including 4\+ years in product management, with AI/ML or GenAI products shipped to production.
- Bachelor’s degree in computer science, engineering, or a related field, or an equivalent combination of experience.
- Hands\-on building: You use AI tools regularly and can articulate specifically what you would change about a model's behavior and why. You prototype your own ideas.
- Evaluation experience: You have built evals, including golden sets, ground truth, and offline and live evals, and used precision\- and recall\-based metrics to make product decisions.
- Systems thinking: When you find a problem, you build the infrastructure that prevents the whole class of problem.
- Communication across domains: You move between business and technical concepts, with a track record of business cases, ROI models, and roadmaps that inform investment decisions.
- AI knowledge: A working understanding of modern AI/ML and GenAI (LLMs, agents, RAG, prompt engineering, and Evaluation methodology) and how it applies to enterprise problems.
Preferred Qualifications
- Experience in healthcare, insurance, or another regulated industry.
- A well\-supported 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.
- Comfort with ambiguity and a fast pace, working from first principles.
Additional Information
This role follows a hybrid work schedule, requiring employees to work three days per week in the office at our New York City location, 1700 Broadway, New York, NY 10019, with the remaining days worked remotely.
To ensure Home or Hybrid Home/Office employees' ability to work effectively, the self\-provided internet service of Home or Hybrid Home/Office employees must meet the following criteria:
At minimum, a download speed of 25 Mbps and an upload speed of 10 Mbps is required; wireless, wired cable or DSL connection is suggested.
Satellite, cellular and microwave connection can be used only if approved by leadership.
Employees who live and work from Home in the state of California, Illinois, Montana, or South Dakota will be provided a bi\-weekly payment for their internet expense.
Humana will provide Home or Hybrid Home/Office employees with telephone equipment appropriate to meet the business requirements for their position/job.
Work from a dedicated space lacking ongoing interruptions to protect member PHI / HIPAA information.
Scheduled Weekly Hours
40Pay 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.
$151,600 \- $208,400 per year
This 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.
Salary Context
This $151K-$208K range is below the median for AI Product Manager roles in our dataset (median: $185K across 167 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 4,317 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At Humana, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills Required
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $217,100 based on 471 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($180K) sits 17% below the category median. Disclosed range: $151K to $208K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Humana AI Hiring
Humana has 8 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager. Positions span New York, NY, US, KY, US, NY, US. Compensation range: $110K - $208K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.