Senior AI Engineer — Generative & Cloud-Native AI

CVS Health; Ohio; Hybrid; USD 83,000 - 204,000; Full time

Job summary

CVS Health in the United States is seeking an experienced AI/ML Engineer to design, develop, and deploy Generative AI applications across the enterprise. You will build cloud-native services, integrate RAG workflows, and collaborate with product owners, data, and security teams to deliver responsible AI solutions.

The role emphasizes security, HIPAA compliance, testing, and scalable APIs. Proficiency in Python, cloud platforms (AWS/GCP), and experience with LLMs and vector databases are

Qualifications

• 5+ years of software engineering, machine learning engineering, or AI engineering experience.
• 2+ years building, deploying, or supporting AI/ML or Generative AI solutions in production.
• Experience with cloud platforms such as AWS or GCP, including serverless services, APIs, event-driven architectures, or cloud-native app development.
• Proficiency in Python and scalable application development.
• Experience with LLMs, prompt engineering, RAG architectures, vector databases, agentic workflows, or equivalent AI technologies.

Responsibilities

• Designs, develops, and deploys AI and Generative AI applications using cloud-native services and modern software engineering practices.
• Builds and maintains AI-powered solutions utilizing technologies such as AWS Bedrock, GCP Vertex AI, large language models (LLMs), and machine learning frameworks.
• Develops Retrieval-Augmented Generation (RAG) systems, including document ingestion, vector search, embeddings, and retrieval pipelines to integrate enterprise knowledge into AI applications.
• Creates, tests, and optimizes prompts, workflows, and agentic AI solutions using technologies such as Bedrock Agents, Vertex AI Agent Builder, LangChain, LangGraph, LlamaIndex, or similar frameworks.
• Develops APIs, microservices, and event-driven integrations that enable scalable and secure AI capabilities across enterprise platforms.
• Collaborates with product owners, engineers, data teams, security teams, and business stakeholders to gather requirements, recommend solutions, and deliver AI capabilities that meet business objectives.
• Writes and executes comprehensive test cases, performs debugging, conducts code reviews, monitors production performance, and resolves issues to ensure reliability and quality.
• Participates in model evaluation, deployment, monitoring, and optimization activities to improve performance, accuracy, latency, scalability, and cost efficiency.
• Implements AI solutions in compliance with security, privacy, governance, and Responsible AI standards, including HIPAA and enterprise data protection requirements.
• Creates and maintains technical documentation, including solution designs, architecture diagrams, implementation guides, and operational runbooks while sharing knowledge with team members.
• Contributes to Agile or SAFe delivery teams by participating in planning sessions, sprint activities, estimation, and continuous improvement initiatives.
• Evaluates new AI technologies, frameworks, and cloud services and recommends opportunities to improve existing solutions and engineering practices.

Skills

Software engineering

Machine learning engineering

AI engineering

Python

LLMs / prompt engineering

RAG architectures

Cloud platforms (AWS / GCP)

Team collaboration

Growth mindset

Execution / delivery

Education

Bachelor's degree or equivalent

Tools

AWS Bedrock

GCP Vertex AI

Azure OpenAI

LangChain

LangGraph

LlamaIndex

Pinecone

OpenSearch

Job description

CVS Health in the United States is seeking an experienced AI/ML Engineer to design, develop, and deploy Generative AI applications across the enterprise. You will build cloud-native services, integrate RAG workflows, and collaborate with product owners, data, and security teams to deliver responsible AI solutions.

The role emphasizes security, HIPAA compliance, testing, and scalable APIs. Proficiency in Python, cloud platforms (AWS/GCP), and experience with LLMs and vector databases are