Software Development Engineer

CVS Health is dedicated to building a more connected and compassionate health experience. They are seeking a Software Development Engineer to join the AI LaunchPad team, focusing on designing and operating production AI systems that enhance healthcare delivery through Generative AI and LLM technologies.

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

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
• 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