Software Development Engineer

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Logo of CVS Health

CVS Health

10,000+ employees

Founded 1963

⚕️ Healthcare Insurance

🛒 Retail

🧘 Wellness

Healthcare Insurance • Retail • Wellness

CVS Health is a leading American healthcare company dedicated to improving health access and affordability. The company focuses on a comprehensive approach that includes health services, health insurance, and pharmacy benefits management. Through its subsidiaries, such as Aetna and CVS Caremark, CVS Health offers a range of services that facilitate wellness, condition management, and affordable prescription drug coverage. CVS Health operates neighborhood pharmacies, provides mail-order pharmacy services, and manages specialty medication programs, aiming to make healthcare convenient and accessible for everyone. Driven by a mission to connect people with essential care services, CVS Health is committed to fostering healthier communities and supporting the wellbeing of all individuals.

📋 Description

• 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.

🏖️ Benefits

• medical, dental, and vision coverage • paid time off • retirement savings options • wellness programs • other resources, based on eligibility

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