Lead AI/ML Engineer - Eden Prairie, MN or Schaumburg, IL

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together. As a Lead AI/ML Engineer within Optum Technology, you will lead the architecture, design, and implementation of high-performance, event-driven backend systems and intelligent automation solutions supporting distributed clinical systems. You will collaborate with cross-functional technology and data teams to deliver secure API solutions, build robust data integration pipelines, automate CI/CD deployments, and establish end-to-end observability. This role offers the opportunity to leverage innovative cloud, streaming, and backend technologies to drive meaningful health outcomes at enterprise scale. 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.

Lead the design, development, and deployment of scalable backend services and AI/ML system integrations across distributed clinical applications Build event-driven backend components using Apache Kafka and integrate with relational databases (Oracle, PostgreSQL, MySQL) utilizing Spring Data JPA and Hibernate Apply deep expertise in API security protocols, including OAuth 2.0, JWT, and OAuth Client Credentials, to secure enterprise microservices and endpoints Lead CI/CD pipeline automation, containerization, and cloud deployment strategies using Docker, Kubernetes, and cloud infrastructure (AWS/Azure) Establish end-to-end monitoring, logging, and performance observability across distributed clinical systems using Splunk, ELK, Prometheus, and Grafana Drive engineering best practices, design reviews, code quality standards, and continuous technical improvement across the engineering team Collaborate with data scientists, software engineers, and product stakeholders to operationalize intelligent solutions into production environments You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

7+ years of experience in AI/ML engineering, software engineering, data engineering, or automation engineering, with hands-on experience delivering production-grade solutions 3+ years of experience building solutions using Large Language Models (LLMs), generative AI, prompt engineering, or retrieval- augmented- systems (RAG) 3+ years of experience building event-driven backend components using Apache Kafka 3+ years of experience working with relational databases (Oracle, PostgreSQL, or MySQL) using Spring Data JPA and Hibernate 3+ years of hands-on experience implementing API security protocols, including OAuth 2.0, JWT, and OAuth Client Credentials 2+ years of experience developing agentic AI systems, including multi-step reasoning workflows, task orchestration, or tool-calling agents Hands-on experience with modern AI orchestration frameworks (e.g., LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or cloud- native AI services). Experience deploying scalable AI solutions within cloud environments(e.g., Azure, AWS, GCP) using microservices, containers, or serverless architectures Preferred Qualifications: Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field Experience integrating machine learning models or AI services into enterprise