Senior Machine Learning Engineer - Generative AI & Full-Stack Applications

Benefits and workplace culture

CVS Health offers a collaborative, data driven environment where senior engineers build GenAI and AI powered capabilities that drive real business outcomes. This on site, Dover, Delaware role partners with business stakeholders and senior technical leaders within CVS Health's Solutions Engineering and Infrastructure AI/ML capability to evaluate, design, implement, and scale AI solutions. The team emphasizes responsible AI practices, practical design, and production readiness to deliver customer focused results.

• Medical, dental, and vision coverage
• Paid time off
• Retirement savings options
• Wellness programs
• Other resources, based on eligibility

Location: Dover, DE onsite. Hours: 40 per week. Time type: Full time. Pay range: USD 83,430 - 222,480 per year.

Responsibilities

• Develop and deploy AI powered services and features that connect enterprise data and systems with large language models and machine learning models.
• Contribute to solution design by proposing approaches, identifying dependencies, and documenting tradeoffs and implementation plans.
• Deliver features using strong engineering practices including test automation, code review, CI/CD, and readiness for production.
• Design and optimize retrieval augmented generation pipelines (retrieval, ranking, grounding) and implement prompt patterns to improve reliability and user experience.
• Contribute to evaluation suites and regression tests to maintain quality and safety over time.
• Implement guardrails and security controls such as 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, including latency, throughput, caching, and model selection.
• Adhere to and reinforce platform standards for deployment, versioning, monitoring, and documentation.
• Collaborate 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.

Requirements

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

Technologies

• Kubernetes
• LLMs
• RAG pipelines
• CI/CD