Interested in this AI/ML Engineer role at CVS Health?
Apply Now →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
CVS Health's Analytics \& Behavior Change (A\&BC) is an organization working to solve some of the most challenging problems at the intersection of technology and healthcare. A\&BC leverages advanced analytics, machine learning, modeling, and a hypothesis\-driven approach to transform data into actionable, customer\-centric insights to drive growth, improve health outcomes and access to health care across all our businesses in CVS Health. Our data teams build next generation data and machine learning platforms and products in the cloud that help CVS Health to make healthier happen for 100\+ million customers.
CVS Health is building the next generation of AI\-powered tools that transform the fundamentals of claims service operations, including solutions such as AI\-powered agentic claims advisor platform and auto adjudication systems and knowledge bases. We are looking for a Director, Product Management\-AI Claims Platform to own this portfolio. You will set the “what” and “why” \- define vision and roadmap, lead a team of Product Managers, each heading a dedicated cross\-functional squad (agile development teams) to deliver measurable impact in a high\-stakes enterprise environment.
This is a rare opportunity to own a flagship AI product in healthcare from strategy through delivery — partnering closely with Business executives, Operations teams, Enterprise technology, Data science and Engineering, with strong visibility to senior leadership. This role requires operating with a high degree of autonomy while maintaining credibility across the stakeholders.
Key Responsibilities:
*Product Strategy \& Vision* (\~40%)
- Own the product vision and multi\-horizon roadmap for AI\-powered claims decision\-support and auto adjudication platform, identifying, shaping and prioritizing capabilities
- Translate complex, nuanced claims policies and business operational workflows into a clear, prioritized technology product strategy across Aetna’s commercial and government lines of businesses
- Ensure user\-centric design and anchor the product strategy and scope to maximize impact and support future scaling
- Make confident, well\-reasoned product decisions amid ambiguity, driving momentum and impact without waiting for perfect information
- Frame investment decisions and tradeoffs for senior executives in terms of measurable outcomes
*Cross\-functional leadership \& operating model* (\~30%)
- Serve as the primary product voice across a highly matrixed enterprise, partnering with business, enterprise technology, data science and engineering, and program leadership.
- Shape how a fast\-scaling product organization operates — clarifying roles, decision\-making, and ways of working across product life cycle activities.
- Build durable, scalable partnerships with business and subject\-matter experts to ensure alignment of vision
- Shape business case and supporting budgeting, investment committee review, and finance reporting processes
- Anticipate and resolve adjacent portfolio dependencies and competing priorities, keeping the broader effort aligned and moving.
- Be primary point of engagement for senior business stakeholders and tailor communication by audience and goals, whether aligning product strategy, driving commercial decisions, or unblocking delivery and anticipating misalignment before it surfaces
*Impact delivery* (\~30%)
- Lead delivery across the portfolio including roadmap, prioritization, milestone, and impact accountability, through a team of product managers, setting clear direction and growing the team while stepping in to perform hands\-on product responsibilities when needed
- Identify and resolve cross\-squad and cross functional interdependencies and prioritization trade\-offs
- Responsible for setting, measuring, and leading the team to accomplish product adoption, user change management and business impact goals
- Engage credibly in technical discussions, ensuring solution feasibility and traceability to business and customer requirements
- Partner closely with engineering and data science on the product’s intelligence engine, data foundations, validation and testing systems, coordinating resolution with broader Enterprise partners
Required Qualifications
- 10\+ years in Product Management, with clear progression to Senior / Director\-level scope and a track record of owning products end\-to\-end.
- 5\+ years of experience turning complex, ambiguous policy or business rules into reliable product logic in partnership with subject\-matter experts.
- 5\+ years leading through influence in complex, matrixed organizations, creating clarity and momentum amid ambiguity.
- 3\+ years’ hands\-on experience building AI or other advanced\-analytics powered workflow\-automation products in real operational environments, including human\-in\-the\-loop systems where accuracy and trust matter.
- 3\+ years of experience with healthcare claims, adjudication systems, or other complex, policy\-driven operational workflows.
- 3\+ years demonstrating skills as a first\-principles thinker who can get to the root of hard problems and translate them into a clear strategy executives can act on.
- 3\+ years of exceptional executive communication — able to distill complex tradeoffs into crisp, compelling narratives for VP\+ audiences.
Preferred Qualifications
- Familiarity with claims adjudication systems and business rules engines.
- Demonstrated ability to design and evolve how a product organization operates.
- Fluency with the latest ML and agentic approaches, with a clear point of view on where human oversight belongs, guardrails and evaluation strategy.
- Change\-management and adoption\-strategy experience for enterprise tools and software.
Education
- Bachelor's degree required, preferably in a quantitative, analytical, or technical field (e.g., Data Science, Statistics, Computer Science, Health Informatics, Economics, or related discipline).
- MBA or advanced degree preferred.
Pay Range
The typical pay range for this role is:
$144,200\.00 \- $288,400\.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. 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: 07/25/2026
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.
Salary Context
This $144K-$288K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At CVS Health, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,150. Disclosed range: $144K to $288K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
CVS Health AI Hiring
CVS Health has 10 open AI roles right now. They're hiring across LLM Engineer, AI/ML Engineer, Data Scientist, AI Software Engineer. Positions span Hartford, CT, US, Richardson, TX, US, Woonsocket, RI, US. Compensation range: $144K - $288K.
Location Context
AI roles in New York pay a median of $220,000 across 1,045 tracked positions.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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