Dir, AI​/ML Engineering - Remote

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 in making healthcare work better for everyone through people-led, responsible AI while Caring. Connecting. Growing together.

As Director, AI/ML Engineering - AI-Ready Data and Context Platforms, you will lead the strategy, architecture, and delivery of the enterprise context layer required to support generative AI and agentic workflows. This role will make enterprise data AI-ready by building semantic models, ontologies, knowledge graphs, metadata capabilities, and reusable contextual data products.

You will partner with AI, data, product, architecture, governance, and business teams to ensure AI agents can access trusted, relevant, secure, and understandable information. The role will also lead multidisciplinary engineering teams and establish standards for context engineering, semantic interoperability, data quality, governance, and AI grounding.

You'll enjoy the flexibility to work remotely
* from anywhere within the U.S. as you take on some tough challenges.

• Lead and direct teams of AI/ML engineers in designing, building, and delivering enterprise-scale machine learning systems and intelligent platforms
• Partner with senior technology, data, analytics, product, and business leaders to embed semantic and contextual foundations into the broader enterprise AI strategy
• Define and own the enterprise strategy and roadmap for AI-ready data, semantic architecture, knowledge graphs, and contextual data platforms
• Establish a clear architectural vision for the enterprise context layer that supports generative AI applications, intelligent search, decision-support systems, and agentic workflows
• Identify the semantic, contextual, and data-quality capabilities required for AI agents to accurately understand business entities, relationships, processes, policies, terminology, and constraints
• Translate enterprise AI priorities into a sequenced portfolio of foundational data, metadata, ontology, and knowledge-graph capabilities
• Use enterprise-approved AI tools to streamline workflows, automate tasks, and drive continuous improvement
• Evaluate emerging trends to inform solution design, platform scalability, and strategic technical innovation
• Mentor and cultivate technical leaders and engineering talent to ensure continuous technical growth and team capability

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 in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field
• 10+ years of experience in AI/ML engineering, data engineering, data architecture, knowledge engineering, or semantic technologies
• 5+ years of experience leading technical teams, influencing senior stakeholders, and translating business needs into platform capabilities
• 5+ years of experience leading enterprise-scale data, AI, or knowledge-platform initiatives
• 3+ years of experience designing semantic models, ontologies, taxonomies, or knowledge graphs
• 3+ years of experience integrating structured and unstructured data into scalable AI-ready…