Interested in this AI Product Manager role at CVS Health?
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About This Role
We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time.
Position Summary
Our team owns the foundational AI/GenAI platform services that power CVS Health's internal agentic and LLM\-driven tooling — including LLM routing and cost governance infrastructure, internal developer tooling for AI\-assisted software development, retrieval\-augmented generation (RAG) capabilities, and orchestration tools for building and deploying agentic workflows. We sit at the intersection of platform engineering and applied GenAI: we're responsible for making it fast, safe, and cost\-effective for engineering teams across the enterprise to build with LLMs, while navigating the compliance realities of operating in a healthcare environment (PHI/PII handling, HIPAA, BAA requirements with model providers). This role will design and build core platform services — spanning areas like auth, quota/cost management, observability, and routing policy — and will help define what our next generation of foundational AI services looks like as the GenAI landscape evolves. The team is deeply senior and highly collaborative; we're looking for someone who brings genuine, self\-driven enthusiasm for this space — someone who explores new ideas and tools because they're excited to, not because they were asked to — while working closely with the rest of the team to bring those ideas to life.
Required Qualifications
- 5\+ years of professional software engineering experience, including 2\+ years building production backend services in Python and/or TypeScript/Node.js
- 2\+ years of experience designing and building RESTful APIs or microservices using frameworks such as FastAPI, Flask, Express, or NestJS
- Experience integrating with one or more LLM/AI provider APIs (e.g., Anthropic, OpenAI, AWS Bedrock, Google Vertex AI) in a production system
- Experience with at least one major cloud provider (AWS, Azure, or GCP)
- Experience with the following (or equivalents): Redis, Kafka, and MongoDB in a production environment
- Experience with OAuth2/OIDC or JWT\-based authentication and authorization systems
- Experience with observability/telemetry tooling (e.g., OpenTelemetry, Prometheus, Grafana, Langfuse, Datadog)
- Experience with containerized applications (Docker) and CI/CD pipelines
- Experience with version control systems (Git) and code review processes
Preferred Qualifications
- Genuine, self\-motivated curiosity about GenAI and emerging AI infrastructure — someone who follows the space on their own and shows up with new ideas, tools, or approaches unprompted
- Strong team player who collaborates readily and shares ideas openly, even while operating on a team of senior engineers with established conventions
- Comfortable respectfully challenging established patterns and proposing alternatives as part of a collaborative team dynamic
- Prior experience building LLM/GenAI infrastructure itself (e.g., LLM gateways, agentic orchestration systems, RAG platforms) — not just consuming provider APIs, but designing the systems around them
- Ability to reason about system design trade\-offs in distributed, stateful systems (e.g., cache invalidation, consumer group rebalancing, blue\-green deployment of stateful services)
- Strong written and verbal communication skills, with the ability to explain technical trade\-offs to both engineers and non\-technical stakeholders
- Comfort operating with ambiguity and evolving requirements in a fast\-moving technical landscape
- Experience or interest in prompt engineering, model routing strategies, or LLM cost optimization techniques
- Experience in a regulated industry (healthcare, finance, or similar), with familiarity around compliance considerations for sensitive data (PHI/PII)
- Interest in eventually growing into technical leadership on a specific platform service
- Collaborative mindset with a bias toward building reusable, well\-documented internal tooling
Education
Bachelor's degree or equivalent work experience in Mathematics, Statistics, Computer Science, Analytics, Engineering, or related discipline. Master's degree preferred
Anticipated Weekly Hours
40Time Type
Full timePay Range
The typical pay range for this role is:
$92,700\.00 \- $185,400\.00
This pay range represents the base hourly rate or base annual full\-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short\-term incentive program in addition to the base pay range listed above.
Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.
Great benefits for great people
We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families.
This full‑time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility.
Additional details about available benefits are provided during the application process and on Benefits Moments.
We anticipate the application window for this opening will close on: 08/14/2026
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.
Salary Context
This $92K-$185K range is in the lower quartile 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 CVS Health, 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 ($139K) sits 36% below the category median. Disclosed range: $92K to $185K.
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.
CVS Health AI Hiring
CVS Health has 6 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager, AI Software Engineer. Positions span New York, NY, US, TX, US, Richardson, TX, US. Compensation range: $185K - $334K.
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
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