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CVS Health
Work at Home, Washington, United States
(on-site)
Posted
1 day ago
CVS Health
Work at Home, Washington, United States
(on-site)
Job Type
Full-Time
Job Function
Other
Software Development Engineer
The insights provided are generated by AI and may contain inaccuracies. Please independently verify any critical information before relying on it.
Software Development Engineer
The insights provided are generated by AI and may contain inaccuracies. Please independently verify any critical information before relying on it.
Description
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.Position Summary
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.
Role
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.
- 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.
Required Qualification
- 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.
Preferred Qualification
- 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.
Anticipated Weekly Hours
40
Time Type
Full time
Pay Range
The typical pay range for this role is:
$79,310.00 - $158,620.00
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 offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above.
Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.
Great benefits for great people
We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families.
This full‑time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility.
Additional details about available benefits are provided during the application process and on Benefits Moments.
We anticipate the application window for this opening will close on: 06/22/2026
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.
Job ID: 83416824
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