Senior Software Development Engineer - GenAI

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

40

Time Type

Full time

Pay 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.