Director of AI​/ML Engineering Remote Nationwide or Hybrid in MN​/DC

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities.

Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

The AI/ML Engineering team within Optum Health Claims, part of Optum Technology, is redefining how healthcare claims are processed at massive scale. This team sits at the intersection of claims platforms, data engineering, observability, and applied AI, driving the transition from manual, rules‑driven operations to intelligent, touchless, and self‑healing claims systems.

As Director of AI/ML Engineering, you will lead a transformation agenda, growing, high‑impact team responsible for building enterprise‑grade AI platforms, claims data pipelines, and operational intelligence capabilities that support tens of millions of claims annually. Your charter spans traditional ML, modern AI techniques, and automation, applied directly to real operational problems‑reducing rework, improving accuracy, lowering SG&A, and accelerating outcomes.

You will partner closely with claims engineering, product, data, operations, enterprise architecture, and business leaders across Optum and United Health Group. The work is hands‑on, highly visible, and outcome‑driven—ideal for a leader excited to build AI as a fabric across healthcare operations, not just models in isolation.

The team operates at enterprise scale, with strong executive sponsorship, mature production platforms, and a mandate to innovate. If you are energized by turning complex data and workflows into measurable operational advantage, this role offers the opportunity to lead meaningful transformation in one of the most critical domains in healthcare.

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 and execution of AI/ML engineering strategy for claims platforms, aligned with business outcomes
• Build and operationalize enterprise data pipelines across multiple claims systems
• Develop and scale observability and operational intelligence suites that surface manual work, rework, exceptions, and automation opportunities
• Apply traditional ML, advanced AI, and intelligent automation to reduce manual claims processing and improve accuracy
• Partner with engineering, product, data, and operations leaders to embed AI directly into end‑to‑end claims workflows
• Establish engineering standards, MLOps practices, and responsible AI patterns for production systems
• Mentor and grow senior engineers and AI practitioners in a high‑expectation, high‑impact environment

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.

• 6+ years of hands on experience with traditional ML techniques (e.g., regression, tree based models, NLP, classical optimization) and modern AI approaches (deep learning, GenAI/LLMs, RAG, agentic AI systems)
• 5+ years of deep experience in data engineering, including data quality management, feature pipelines, analytical pipelines, and ML data readiness at scale
• 5+ years of experience leading and scaling engineering teams (typically 10-40+ engineers/data scientists) delivering production AI/ML systems with clear ownership of reliability, cost, performance, and business outcomes
• 4+ years of proven ability to translate complex operational problems into production grade, scalable AI/ML solutions embedded in enterprise workflows
• 3+ years of solid, hands on…