Senior AI ML Engineer - Remote

UnitedHealth Group•Eden Prairie, MN

15h•$120,100 - $214,500•Remote

About The Position

As a Senior AI/ML Engineer within the Optum Health & Financial Tech AI team, you will design and build enterprise-scale generative AI applications and agentic workflows that solve complex health and financial technology challenges. You will collaborate with cross-functional partners to develop multi-step reasoning systems, implement advanced Retrieval-Augmented Generation (RAG) pipelines, and craft responsive, full-stack experiences using modern frameworks like React, Next.js, Python, and PostgreSQL. By deploying innovative AI technologies safely and responsibly, you will directly support our mission of delivering impactful, context-aware digital solutions that improve health outcomes and operational efficiency. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

Requirements

Bachelor's degree or equivalent experience (such as an additional 4+ years of software development experience in lieu of a degree)
6+ years of professional experience in software engineering or AI/ML engineering
4+ years of hands-on experience with frontend technologies (React, Nextjs) and backend development (Python or Nodejs, and REST APIs)
3+ years of experience with relational database design and optimization using PostgreSQL
2+ years of experience building and deploying end-to-end Generative AI and LLM-powered applications in production
2+ years of experience designing and implementing RAG (Retrieval-Augmented Generation) pipelines, including semantic search, embeddings, and vector databases
1+ years of experience with AI orchestration frameworks (such as LangChain, LangGraph, or CrewAI) or developing agentic, multi-agent AI workflows

Nice To Haves

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field
Experience implementing hybrid search strategies, GraphRAG, and contextual enrichment patterns for document retrieval
Deep understanding of distributed systems, microservices architecture, and enterprise application scalability
Solid expertise in designing AI evaluation metrics and establishing safety guardrails for reliable model outputs
Proven ability to mentor engineering teams, lead technical design reviews, and establish best practices in full-stack and AI development
Proven excellent cross-functional communication skills, with the ability to translate complex technical AI concepts into clear business insights for stakeholders

Responsibilities

Design, develop, and deploy enterprise-scale AI-powered solutions and LLM-powered applications using modern GenAI frameworks and APIs with an emphasis on the responsible use of AI
Develop agentic AI workflows, multi-step reasoning systems (with tool usage and memory), and advanced Retrieval-Augmented Generation (RAG) pipelines
Design and develop responsive frontend applications using React and Nextjs, and build backend services, APIs, and microservices using Python and Nodejs
Build systems for document ingestion, chunking, embeddings, semantic search, and advanced retrieval strategies (hybrid search, GraphRAG, contextual enrichment)
Design and optimize relational data models using PostgreSQL and integrate vector databases with relational data sources for contextual responses
Define end-to-end architecture spanning frontend, backend, AI, and data layers, ensuring performance, scalability, and reliability
Lead technical decision-making, design reviews, and code reviews, while mentoring junior engineers in AI engineering and full-stack best practices
Use enterprise-approved AI tools to streamline developer workflows, automate tasks, and drive continuous improvement across the development lifecycle
Evaluate emerging AI trends, frameworks, tools, and technologies to inform solution design, strategic innovation, and technical direction
Collaborate with product, business, and engineering teams to translate complex business requirements into scalable technical designs, communicating complex AI concepts to non-technical stakeholders