Enterprise AI & LLM Engineer | RAG Systems

CVS Health Corporation; United States; Remote; USD 83,000 - 204,000; Full time

Job summary

CVS Health Corporation in the United States is seeking an experienced AI/LLM Engineer to design, develop, and operationalize enterprise-grade language-model–powered applications. You will build text-based reasoning, RAG pipelines, and scalable prompt frameworks that improve decision making, automation, and knowledge discovery across the organization.

Collaborate with business stakeholders to translate requirements into reliable, explainable AI solutions, ensuring security, governance, and

Qualifications

• Strong programming experience in Python and familiarity with software engineering best practices.
• Hands-on experience building production-grade AI/ML systems, not just prototypes.
• Experience working with Large Language Models (LLMs) and APIs.
• Solid understanding of NLP fundamentals and machine learning concepts.
• Practical experience with Retrieval-Augmented Generation (RAG) systems and embeddings/vector search.
• Experience designing and implementing APIs, microservices, or distributed systems.
• Familiarity with model evaluation techniques and performance metrics.
• Strong debugging and problem-solving skills in complex systems.

Skills

Python

Production-grade AI/ML

LLMs/APIs

NLP fundamentals

Machine learning concepts

RAG systems

Prompt engineering

Embeddings & vector search

APIs / microservices

Model evaluation

Debugging

Education

Bachelor’s/Master’s in CS/Engineering/Data Science

Tools

LangChain

LlamaIndex

Semantic Kernel

Pinecone

Weaviate

FAISS

MongoDB Atlas Vector Search

Spark

Pandas

FastAPI

Flask

AWS

Azure

GCP

Docker

Kubernetes

Job description

CVS Health Corporation in the United States is seeking an experienced AI/LLM Engineer to design, develop, and operationalize enterprise-grade language-model–powered applications. You will build text-based reasoning, RAG pipelines, and scalable prompt frameworks that improve decision making, automation, and knowledge discovery across the organization.

Collaborate with business stakeholders to translate requirements into reliable, explainable AI solutions, ensuring security, governance, and