AI/LLM Engineer

As a key member of a cross-functional team, you will collaborate with business stakeholders to translate business requirements into reliable, explainable, and production-ready AI solutions. You will play a critical role in shaping enterprise AI capabilities by ensuring solutions are secure, responsible, and optimized for real-world performance.

• Design and implement LLM-powered applications that support complex, text-based reasoning and decision workflows.
• Develop and refine chain-of-thought-style reasoning approaches and structured prompt patterns to improve model accuracy and interpretability.
• Architect and build Retrieval-Augmented Generation (RAG) systems leveraging embeddings, vector search, and hybrid retrieval strategies.
• Create, evaluate, and optimize prompt engineering frameworks, including reusable templates, prompt libraries, and testing methodologies.
• Implement monitoring, logging, and feedback loops for continuous improvement of AI systems.
• Ensure compliance with security, governance, and Responsible AI principles.
• Partner with product and analytics teams to rapidly prototype and iterate AI-driven features.

Tools & Technologies

• Programming: Python (primary), SQL
• LLM Platforms: OpenAI, Anthropic, Google Vertex AI
• Frameworks: LangChain, LlamaIndex, Semantic Kernel
• Vector Databases: Pinecone, Weaviate, FAISS, MongoDB Atlas Vector Search
• Data Processing: Spark, Pandas
• APIs & Services: FastAPI, Flask, REST/gRPC
• Cloud Platforms: AWS, Azure, Google Cloud Platform (Google Cloud Platform)
• DevOps & MLOps: Docker, Kubernetes, CI/CD tools
• Monitoring & Evaluation: Prompt evaluation tools, logging frameworks, observability platforms

• 5+ years expereince
• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience.
• 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:
• Natural Language Processing (NLP) fundamentals
• Machine learning concepts (training, evaluation, overfitting, bias)
• Practical experience with:
• Retrieval-Augmented Generation (RAG) systems
• Prompt engineering and prompt optimization
• Embeddings and 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., * Experience with LLM platforms such as OpenAI, Anthropic, Google Vertex AI, or similar.
• Familiarity with orchestration frameworks like LangChain, LlamaIndex, Semantic Kernel, or equivalent.
• Experience with vector databases (e.g., Pinecone, Weaviate, FAISS, MongoDB Atlas Vector Search).
• Knowledge of MLOps practices, including CI/CD pipelines for AI systems.
• Experience deploying solutions in cloud environments (e.g., AWS, Azure, Google Cloud Platform).
• Exposure to agent-based architectures or multi-step AI workflows.
• Experience in financial services enterprise environments (or similar data-intensive industries).
• Experience with evaluation frameworks and benchmarking for LLMs.

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.