Software Development Engineer

CVS Health•Washington, DC

1d•Onsite

About The Position

AI LaunchPad is CVS Health's centralized AI platform for the HCD Business Unit. We provide LLM access, observability tooling, and the infrastructure needed to build and deploy production-grade AI agents across the enterprise. Our engineers work at the intersection of cutting-edge generative AI research and real-world healthcare impact — shipping agentic systems, RAG pipelines, and multimodal workflows that touch millions of patients and providers. We are looking for a Software Engineer with a strong Generative AI and LLM engineering background to join the AI LaunchPad team. You will design, build, and operate production AI systems — from agentic orchestration pipelines and RAG architectures to LLM evaluation frameworks and MLOps infrastructure. You will have a direct hand in reducing the POC-to-production cycle time and accelerating AI adoption across HCD.

Requirements

3+ years of software engineering experience with at least 1 year focused on production Generative AI or LLM systems.
Hands-on experience with agentic AI frameworks: LangGraph, LangChain, CrewAI, or ADK.
Demonstrated expertise building and evaluating RAG systems (hybrid search, chunking strategies, eval pipelines).
Proficiency with cloud ML platforms: GCP Vertex AI, AWS SageMaker, or equivalent.
Strong Python skills; experience with ML libraries (Transformers, fine-tuning with LoRA, multimodal models).
Experience with MLOps tooling: CI/CD pipelines, Docker, Kubernetes, Terraform, and observability stacks.
Familiarity with data engineering tools: Spark, Airflow, SQL, distributed pipelines.
Understanding of healthcare data privacy requirements (HIPAA) and secure AI deployment practices.

Nice To Haves

M.S. or Ph.D. in Computer Science, Data Science, or a related field-or equivalent relevant work experience.
Experience with LLM evaluation frameworks: RAGAS, LangFuse, prompt regression testing.
Familiarity with fine-tuning techniques (LoRA, PEFT) and multimodal model architectures.
Prior work in healthcare AI, pharma, or other regulated industries.
Published research or open-source contributions in AI/ML.
Experience with DuckDB, structured reasoning over tabular data, or business intelligence automation.

Responsibilities

Design and deploy enterprise-scale Generative AI platforms including agentic RAG pipelines, multimodal workflows, and LLM-powered automation in HIPAA-compliant cloud environments.
Build and maintain agentic orchestration systems using frameworks such as LangGraph, LangChain, CrewAI, or Google Agent Development Kit (ADK).
Develop and operationalize RAG systems with advanced retrieval techniques (hybrid search, reranking, query rewriting) and robust evaluation pipelines.
Establish LLM observability and CI/CD guardrails — integrating tools like LangFuse and RAGAS — to enable prompt regression detection and production stability.
Implement MLOps best practices including containerization (Docker/Kubernetes), infrastructure-as-code (Terraform), and automated deployment pipelines on GCP (Vertex AI, GKE, Cloud Run) or AWS (SageMaker).
Collaborate with data engineers to design distributed data pipelines (Spark, Airflow, DuckDB) that feed production AI systems at scale.
Partner with product and business teams to translate healthcare use cases into scalable AI solutions that deliver measurable ROI.
Mentor junior engineers, contribute to GenAI/MLOps standards, and drive team-wide adoption of scalable AI practices.
Conduct model evaluation and interpretability analysis (SHAP, LIME, RAGAS) to ensure reliability, fairness, and compliance of deployed models.