Senior Al Engineer

CVS Health

5d•$83,430 - $203,940

About The Position

CVS Health is hiring a Senior AI Engineer to design, develop, implement, deploy, and support AI and Generative AI solutions across affiliate lines of business. The role applies advanced software engineering and machine learning expertise to build scalable AI applications, cloud-native services, and intelligent automation that deliver business value securely and responsibly. The work may use AWS Bedrock, GCP Vertex AI, Retrieval-Augmented Generation (RAG), agentic AI frameworks, and cloud-native architectures to address business challenges. The engineer collaborates with product owners, engineering, data, security, and business teams to define requirements and deliver AI capabilities. Responsibilities also include testing, debugging, code reviews, production monitoring, model evaluation and optimization, compliance with security and Responsible AI requirements, technical documentation, Agile or SAFe delivery, and evaluating emerging AI technologies. The role requires at least five years of relevant engineering experience and at least two years building, deploying, or supporting AI/ML or Generative AI solutions in production. A bachelor's degree or equivalent experience is required.

Requirements

At least 5 years of software engineering, machine learning engineering, or AI engineering experience.
At least 2 years of experience building, deploying, or supporting AI/ML or Generative AI solutions in a production environment.
Experience with AWS or GCP, including serverless services, APIs, event-driven architectures, or cloud-native application development.
Proficiency in Python and experience developing scalable applications using modern software engineering practices.
Experience with LLMs, prompt engineering, RAG architectures, vector databases, agentic workflows, or equivalent AI technologies.
Problem-solving and decision-making skills.
Collaboration and teamwork skills.
Growth mindset, including agility and developing yourself and others.
Execution and delivery skills, including planning, delivering, and supporting.
Bachelor's degree or equivalent experience (high school diploma plus 4 years of relevant experience).

Nice To Haves

Hands-on experience with AWS Bedrock, GCP Vertex AI, Azure OpenAI, or similar AI platforms.
Experience building RAG solutions with vector databases such as OpenSearch, Pinecone, pgvector, or FAISS.
Experience developing AI agents using Copilot Studio, Power Automate, LangChain, LangGraph, LlamaIndex, or similar frameworks.
Experience developing cloud-native APIs, microservices, and event-driven architectures.
Knowledge of Responsible AI, model evaluation, observability, LLM security, and governance practices.
Agile and/or SAFe experience in large enterprise environments.
AWS, GCP, Azure, AI, or Machine Learning certifications.
Healthcare experience.

Responsibilities

Design, develop, and deploy AI and Generative AI applications using cloud-native services and modern software engineering practices.
Build and maintain AI-powered solutions using technologies such as AWS Bedrock, GCP Vertex AI, large language models, and machine learning frameworks.
Develop Retrieval-Augmented Generation systems, including document ingestion, vector search, embeddings, and retrieval pipelines.
Create, test, and optimize prompts, workflows, and agentic AI solutions using frameworks such as Bedrock Agents, Vertex AI Agent Builder, LangChain, LangGraph, and LlamaIndex.
Develop APIs, microservices, and event-driven integrations for scalable and secure AI capabilities across enterprise platforms.
Collaborate with product owners, engineers, data teams, security teams, and business stakeholders to gather requirements, recommend solutions, and deliver AI capabilities.
Write and execute test cases, debug, conduct code reviews, monitor production performance, and resolve issues.
Participate in model evaluation, deployment, monitoring, and optimization to improve performance, accuracy, latency, scalability, and cost efficiency.
Implement solutions in compliance with security, privacy, governance, Responsible AI, HIPAA, and enterprise data protection requirements.
Create and maintain technical documentation, including solution designs, architecture diagrams, implementation guides, and operational runbooks; share knowledge with team members.
Participate in Agile or SAFe planning, sprint activities, estimation, and continuous improvement.
Evaluate AI technologies, frameworks, and cloud services and recommend improvements to solutions and engineering practices.