Lead AI​/ML Engineer - Remote Nationwide or Hybrid in MN​/DC

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 the Consumer Engineering division of the Chief Digital Office (CDO), you will play a critical role in shaping the future of our digital health platforms. This role is designed for a high‑performing engineer with strong software fundamentals and a deep passion for building production‑ready, scalable AI services. You will focus on the practical application of Generative AI techniques, designing end‑to‑end solutions that integrate seamlessly into our enterprise ecosystem.

By leveraging modern data platforms and cloud‑native architectures, you will help bridge the gap between complex machine learning research and reliable, consumer‑facing applications that improve the lives of those we serve.

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 complex AI‑powered solutions to address enterprise‑level business challenges, with focus on responsible AI practices
• Provide technical leadership and architectural guidance to engineering teams building and operating machine‑learning models in production environments
• Use enterprise‑approved AI tools to streamline workflows, automate tasks and foster a culture of continuous improvement and strategic innovation
• Architect and implement scalable AI services, APIs, and pipelines, ensuring they meet rigorous enterprise standards for reliability and performance
• Evaluate emerging AI/ML trends and technologies to inform strategic solution design and lead technical innovation across the organization
• Establish and mature MLOps practices, including enterprise‑grade CI/CD, comprehensive monitoring, and versioning for AI assets
• Design and implement sophisticated AI techniques (e.g., NLP, deep learning, predictive modeling) integrated with large‑scale data and distributed compute platforms
• Ensure all AI solutions strictly adhere to security, privacy, and regulatory standards, upholding the highest principles of responsible AI within a healthcare context
• Mentor junior and mid‑level engineers, providing code reviews and technical guidance to grow team capabilities
• Partner with senior leadership, product managers, and data scientists to align AI initiatives with long‑term business goals

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.

• Bachelor's degree or equivalent experience
• 8+ years of professional software engineering experience delivering high‑quality, production‑grade commercial applications
• 4+ years of AI/ML engineering experience, including designing and deploying models at scale
• 2+ years of experience in a technical lead or architectural role, providing guidance to engineering teams
• 5+ years of hands‑on experience with Python, Java, and SQL
• 2+ years of experience with cloud‑native architectures (specifically AWS, Azure or GCP)
• 2+ years of experience with Databricks, PySpark, and large‑scale data pipeline implementation
• Experience with containerization (Docker/Kubernetes) and building/maintaining enterprise‑grade CI/CD pipelines

• Expertise in Generative AI solutions, specifically utilizing RAG, Lang Chain, and Vector Databases
• Experience with big data technologies such as Spark, Hadoop, and Kafka
• Solid knowledge of Infrastructure as Code (Terraform or Cloud Formation)
• Experience…