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.
CVS Health is seeking a Staff Software Engineer with a strong background in enterprise software architecture, full\-stack application development and building cloud\-native and Agentic AI/Gen AI products. This role will serve as a senior technical leader and a hands\-on engineer responsible for designing, building, and modernizing mission\-critical technology solutions for the Claims Adjudication organization.
The ideal candidate will have expertise in enterprise software engineering, strong architecture background, hands\-on programming experience and a practical experience building production grade Generative AI and Agentic AI solutions. This role will be instrumental in advancing CVS Health’s transition toward modern, AI\-driven, cloud\-native platforms while ensuring continued reliability and integration with existing legacy systems such as IBMi/AS400\.
This role requires a strong balance of technical strategy, architecture leadership, hands\-on coding, engineering execution, stakeholder communication, and production operational excellence.
\*\*We will consider remote US for the right candidate
Key Responsibilities
- Lead the architecture, design, and implementation of scalable, secure, resilient, and maintainable enterprise software solutions.
- Establish architecture principles, design patterns, reference architectures, engineering standards, and technical guardrails.
- Lead architecture reviews, design discussions, and technical decision\-making forums
with engineering teams, architects, product partners, and leadership.
- Design, develop, and deploy cloud\-native solutions such as API, micro services, CI/CD pipelines and real\-time streaming on public cloud platforms, preferably Azure or GCP.
- Remain actively hands\-on in software design, coding, code reviews, debugging, troubleshooting
- Design, implement, and improve CI/CD pipelines for automated build, test, security scanning, deployment, and release management.
- Partner with business and technology teams to identify high\-value AI use cases and translate them into scalable technical solutions.
- Design, build, and deploy enterprise\-grade Agentic AI and Generative AI solutions translating SDLC to ADLC.
- Support model evaluation, prompt evaluation, response quality assessment, guardrails, responsible AI practices, and AI governance
- Integrate LLMs, AI/ML models, vector stores, orchestration frameworks, and cloud\-native services into enterprise applications
- Communicate complex technical concepts clearly to engineering teams, architects, product owners, business stakeholders, and senior leadership Partner with cross\-functional teams to align technology execution with business outcomes.
Required Qualifications
7\+ years of software engineering experience, including significant experience designing and building enterprise\-scale software systems including:
- Strong architecture experience across distributed systems, micro services, APIs, event\-driven architecture, domain\-driven design, and cloud\-native platforms.
- Hands\-on experience building applications in Python, Java , React and other open source frameworks.
- 2\+ years of experience designing or implementing Generative AI, Agentic AI, LLM\-based, or AI/ML\-enabled applications.
- Experience with Enterprise RAG patterns, vector databases, embeddings, prompt engineering, AI orchestration, and AI application integration
- Experience implementing CI/CD pipelines and DevSecOps practices using tools such as Azure DevOps, GitHub Actions, Jenkins, GitLab CI/CD, or equivalent
- Exposure to observability practices including logging, tracing, monitoring, reporting and production troubleshooting. Strong verbal and written communication skills with the ability to influence technical and non\-technical stakeholders.
- Experience leading complex technical initiatives, setting technical direction, mentoring engineers, and driving execution across teams.
Preferred Qualifications
- 10\+ years leading concurrent technical projects in both legacy IBMi/AS400 or similar and emerging technologies
- Experience leading complex technical initiatives, setting technical direction, mentoring engineers, and driving execution across teams.
- Health care industry domain knowledge
- Experience with RxClaim or other PBM adjudication systems
- Experience with Agentic AI frameworks such as Semantic Kernel, LangGraph, LangChain, AutoGen, CrewAI, or equivalent .
- Experience leading enterprise AI transformation initiatives, establishing AI engineering best practices, and defining standards for Agentic AI and Generative AI adoption.
- Experience designing and implementing AI Agents using tool calling, reasoning frameworks, workflow orchestration, multi\-agent systems, and autonomous execution patterns.
Education
Bachelor’s degree or equivalent experience
Pay Range
The typical pay range for this role is:
$118,450\.00 \- $260,590\.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. This position also includes an award target in the company’s equity award program.
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: 09/03/2026
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.
Salary Context
This $118K-$260K range is above 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 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 ($189K) sits 13% below the category median. Disclosed range: $118K to $260K.
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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