Director AI or ML Engineering

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. AI/ML Engineers code and develop software that deploys ML models and algorithms in production. Communicate and present complex analytics results and concepts to leadership and internal stakeholders. Employee AI and/or ML that may include natural language processing (NLP), natural language understanding (NLU), semantic understanding, intent classification, computer vision, deep learning, and automatic speech recognition (ASR). Applies deep learning technologies to give computers that capability to visualize, learn and respond to complex situations. May adapt machine learning to areas such as artificial intelligence, robotics and other products that allow users to have an interactive experience. Work with large scale computing frameworks, data analysis systems. Employees in this role are expected to apply knowledge of experimental methodologies, statistics, optimization, probability theory and machine learning using code for tool building, statistical analysis, using both general purpose software and statistical languages. AI/ML Applied Scientists specialize in advancing and applying artificial intelligence through research-driven, experimental research, and translate research findings into practical AI solutions for the organization.

Define and own the engineering AI strategy to measurably accelerate software development, quality, reliability, and operational efficiency through the use of AI agents Partner with engineering teams to analyze current workflows, development activities, and pain points across the SDLC, identifying high value opportunities where AI agents can deliver meaningful impact Develop a clear, prioritized roadmap of AI agent use cases aligned to business objectives, engineering strategy, and enterprise technology standards Build data driven proposals and business cases for AI agent investments, including baseline measurements, expected productivity gains, cost avoidance, quality improvements, and adoption metrics Lead the design, development, and deployment of AI agents that augment or automate engineering work (e.g., requirements analysis, design support, coding, testing, deployment, reliability, incident analysis) Oversee the end to end lifecycle of AI agents from proof of value through scaled production deployment, ensuring solutions are reliable, secure, observable, and maintainable Establish measurement frameworks, analytics, and KPIs to track realized value and continuously refine AI solutions based on usage, outcomes, and feedback Define a repeatable operating model for how engineering teams identify, build, govern, and adopt AI agents at scale Ensure all AI solutions adhere to enterprise architecture, security, privacy, regulatory, and responsible AI standards, including appropriate human in the loop controls Drive engineering enablement and change management, helping teams adopt new AI enabled ways of working and build confidence using AI as a force multiplier Serve as a trusted advisor and thought leader to engineering and technology leadership, translating complex AI concepts into clear decisions, trade offs, and business outcomes Collaborate closely with architecture, platform, product, data, and security partners to align AI agent strategy with broader enterprise initiatives Provides leadership to and is accountable for the performance and direction through multiple layers of management and