Senior Machine Learning Engineer – Generative AI & Full-Stack

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.

At CVS Health, our purpose is to deliver better health outcomes by meeting consumers where they are—through local care, digital experiences, and a nationwide team committed to quality, safety, and affordability.

Our Solutions Engineering and Infrastructure organization is building an enterprise AI/ML capability that delivers reliable, responsible, and secure AI-powered platforms and solutions at Fortune 5 scale, and this role is foundational to help us develop that capability.

This is an experienced individual‑contributor role focused on evaluating, documenting, building and scaling GenAI and AI-powered capabilities, contributing to solution design, implementation, and production support in partnership with business partners and senior technical leaders.

Implement AI-powered services and application features that integrate enterprise data and systems with LLMs and ML models. Contribute to solution design by proposing approaches, identifying dependencies, and documenting tradeoffs and implementation plans. Deliver features using strong engineering practices: test automation, code review, CI/CD, and operational readiness.

Build and tune RAG pipelines (retrieval, ranking, grounding) and implement prompt patterns that improve reliability and user experience. Contribute to evaluation suites and regression testing to ensure quality and safety over time. Implement guardrails and security controls (input/output validation, policy filtering, and data protection patterns) under guidance from senior engineers.

Instrument services with metrics, traces, logs, and dashboards; participate in incident response and post-incident improvements. Support performance and cost optimization efforts (latency, throughput, caching, and model selection). Follow and reinforce platform standards for deployment, versioning, monitoring, and documentation.

Work closely with product, design, security, and platform teams to refine requirements and deliver customer-focused outcomes. Mentor engineers at earlier career stages and share practical learnings with the broader AI/ML community of practice. Stay current on GenAI and ML platform trends; propose incremental improvements that raise quality and accelerate delivery.

• 5+ years of software engineering experience delivering production systems, including modern APIs and application development.
• 3+ years of experience applying ML/AI concepts in real systems;
  GenAI exposure (LLMs, RAG, evaluation) strongly preferred.
• 3+ years of experience delivering solutions in high‑scale, high‑availability environments with strong security and compliance requirements.

• Proficiency in backend engineering (APIs, services) and comfort contributing across the stack when needed.
• Working knowledge of LLM application development (prompting, RAG, tool calling) and evaluation practices.
• Experience with CI/CD, testing, containerization, and basic Kubernetes concepts.
• Strong debugging and operational skills; ability to improve reliability and performance based on telemetry and root cause analysis.
• Effective collaboration and communication skills across technical and non‑technical stakeholders.

Bachelor’s degree or equivalent experience (High School Diploma and 4 years relevant experience)

Anticipated Weekly

Hours:

40

Time Type:
Full time

The typical pay range for this role is: $83,430.00 – $. 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…