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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.
The Cost Estimation and Navigation AI portfolio at CVS Health is seeking a Staff Software Development Engineer to help build solutions that simplify healthcare navigation and improve the experience for the people we serve.
This portfolio includes Cost Estimator, Benefit Quoting, and Digital Consumer Products, supporting key moments across the healthcare journey from plan selection through active care navigation. These solutions help members, prospective members, customer service agents, and providers access clearer information about cost, benefits, and care options so they can make more informed decisions.
As a Staff Software Development Engineer, you will help design, build, and deliver modern cloud-based applications within a complex distributed systems environment on Google Cloud Platform. You will contribute across architecture, system design, and implementation, helping deliver scalable, reliable solutions while strengthening the long-term technical foundation of the portfolio.
This role offers the opportunity to work on high-impact products that support healthcare decisions and make complex information more accessible and actionable for a broad set of users.
Responsibilities
- Lead the design, development, and delivery of scalable software solutions within the Cost Estimation & Navigation AI portfolio
- Drive architecture and technical design across distributed services, APIs, and platform components to support scalability, resiliency, security, and long-term maintainability
- Partner with product, data science, and engineering teams to translate business priorities and portfolio use cases into production-ready technical solutions
- Provide technical leadership across complex initiatives by guiding implementation decisions, managing dependencies, and addressing engineering tradeoffs
- Design, build, and enhance cloud-native applications, microservices, and APIs using modern service, interface, and messaging patterns
- Define and ensure achievement of non-functional requirements, including performance, availability, failover, scalability, and security
- Evaluate existing architectures and recommend improvements to reliability, operability, flexibility, and cost efficiency
- Lead proof-of-concept development and technical exploration for emerging technologies, including AI/GenAI-enabled capabilities relevant to portfolio needs
- Apply knowledge of data and analytics technologies, including orchestration, non-relational data stores, caching, and large-scale service integration patterns
- Mentor engineers and contribute to engineering excellence through design reviews, code reviews, and technical guidance
- Communicate effectively with technical and non-technical stakeholders to build alignment across teams and organizational boundaries
- Ensure solutions are designed and delivered in compliance with regulatory, privacy, and security requirements, including secure handling of PII and PHI data
Required Qualifications
- 7+ years of experience delivering enterprise-scale software solutions in distributed systems environments
- 5+ years of experience in one or more programming languages such as Java, Python, Go, or JavaScript
- 5+ years of hands-on experience designing, building, and operating cloud-based enterprise solutions
- 5+ years of experience designing and developing modern microservices and scalable, cost-effective APIs
- 3+ years of experience with CI/CD pipelines, automated testing, and DevOps practices
- 3+ years of experience with containerization and orchestration technologies such as Docker and Kubernetes
- Experience working with AI/GenAI platforms and applying intelligent capabilities within software products
Preferred Qualifications
- Healthcare domain experience
- Experience building and operating solutions on Google Cloud Platform, including GKE, Cloud Run, Cloud Build, Pub/Sub, Cloud SQL, and IAM
- Strong understanding of software design principles, distributed systems, and scalable architecture patterns
- Experience influencing technical direction, engineering standards, and solution design across teams or domains
- Experience with ETL processes, data quality practices, and healthcare data management
- Hands-on experience developing user-facing features and applications
- Experience implementing monitoring and observability solutions using OpenTelemetry, Grafana, or similar platforms
- Ability to create and execute roadmaps that balance delivery, innovation, and reliable scale
- Strong collaboration, communication, and stakeholder management skills across organizational boundaries
Education
- Bachelor’s degree in Computer Science or a related field, or equivalent experience (HS diploma + 4 years relevant experience)
Pay Range
The typical pay range for this role is:
$106,605.00 - $284,280.00
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: 10/22/2026 Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.
Salary Context
This $106K-$284K range is above the median for AI Product Manager roles in our dataset (median: $193K across 99 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 9,653 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 $220,200 based on 862 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. This role's midpoint ($195K) sits 11% below the category median. Disclosed range: $106K to $284K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
CVS Health AI Hiring
CVS Health has 10 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer, MLOps Engineer, AI Software Engineer. Positions span UT, US, Tallahassee, FL, US, TX, US. Compensation range: $231K - $334K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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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