Associate AI/ML Engineer

Role Overview

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. As an Associate AI/ML Engineer, you will design, develop, and deploy Agentic AI solutions, build RAG-based applications, and integrate AI capabilities into enterprise applications to improve health outcomes and operational efficiency.

Responsibilities

• Design, develop, and deploy Agentic AI solutions using LLMs, tools, memory, orchestration, and multi-step reasoning workflows
• Build and maintain RAG-based applications using vector databases, embeddings, document ingestion pipelines, retrieval strategies, and prompt engineering
• Develop AI-powered workflow automation solutions to improve operational efficiency and business process intelligence
• Work with frameworks such as Spring AI, LangChain, LangGraph, and related AI orchestration tools
• Integrate AI capabilities into enterprise applications, APIs, microservices, and cloud-native platforms
• Build scalable backend services using Java/Spring Boot and/or Python-based AI frameworks
• Implement prompt engineering, evaluation, guardrails, observability, and monitoring for AI applications
• Work with cloud services on AWS and/or Azure, including AI/ML services, storage, compute, serverless, containerization, and deployment pipelines
• Collaborate with product owners, architects, data engineers, and business stakeholders to understand requirements and deliver AI solutions
• Ensure AI solutions follow security, compliance, privacy, and responsible-AI best practices

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, AI/ML, or a related field
• 3+ years of software engineering experience, with hands-on work building AI/GenAI or LLM-based applications
• Practical experience integrating LLMs via APIs (e.g., OpenAI, Azure OpenAI, Anthropic, Amazon Bedrock)
• Working experience with at least one GenAI framework such as Spring AI, LangChain, or LangGraph
• Experience using at least one vector database (e.g., Pinecone, Weaviate, Milvus, Chroma, FAISS, OpenSearch, or Azure AI Search)
• Hands-on cloud experience with AWS or Azure
• Solid programming skills in Java/Spring Boot and/or Python
• Understanding of RAG fundamentals: embeddings, chunking, retrieval, vector search, and prompt engineering
• Solid understanding of REST APIs and microservices
• Familiarity with Git, CI/CD pipelines, and Docker

Skills

• Python
• Java/Spring Boot
• LangChain
• AWS
• Vector Databases