Senior Director AI 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.

Primary Responsibilities:

• Strategic Leadership Portfolio Oversight
  • Define and drive the AI/ML engineering vision, strategy, and execution roadmap for Healthcare and Life Sciences aligned to enterprise priorities and client transformation agendas
  • Lead a portfolio of multiple concurrent client engagements, ensuring strategic alignment, delivery excellence, financial performance, and customer satisfaction
  • Identify opportunities to expand AI/ML adoption across healthcare and life sciences use cases, including clinical, operational, research, and commercial domains
  • Partner with business leaders to build long-term strategies for scaling AI-powered products, platforms, and services
  • Provide executive oversight for complex AI programs from ideation through deployment, adoption, and value realization
• Client Engagement Executive Relationship Management
  • Serve as a senior executive sponsor and trusted advisor for clients across healthcare and life sciences engagements
  • Engage directly with client leadership to understand strategic priorities, business challenges, and innovation opportunities, translating them into actionable AI solution roadmaps
  • Lead executive-level discussions, solution presentations, strategic workshops, QBRs, and transformation reviews with internal and external stakeholders
  • Drive client confidence through proactive communication, transparent governance, and measurable delivery outcomes
  • Identify growth opportunities within existing accounts and support business development through AI solution positioning, proposal reviews, and strategic pursuit leadership
• AI/ML Solution Leadership
  • Oversee the design, development, and deployment of scalable, secure, and production-grade AI/ML solutions across a variety of healthcare and life sciences use cases
  • Drive the adoption of advanced AI capabilities such as:
    • Machine Learning and Predictive Analytics
    • Natural Language Processing (NLP) / Natural Language Understanding (NLU)
    • Deep Learning
    • Computer Vision
    • Speech/Language AI
    • Generative AI and Large Language Models (LLMs)
    • Intelligent Automation and Decision Support
  • Ensure solutions are architected for scalability, maintainability, explainability, and regulatory readiness
  • Guide teams on applying AI responsibly, including model governance, fairness, observability, and risk mitigation
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• Undergraduate degree or equivalent experience
• Typically 15+ years of overall experience, with significant leadership experience in AI/ML engineering, advanced analytics, digital transformation, or data-driven product/solution delivery
• Experience leading teams working with platforms and frameworks such as TensorFlow, PyTorch, Scikit-learn, and cloud ecosystems such as Azure, AWS, or GCP
• Solid technical depth in:
  • Machine Learning and Deep Learning
  • NLP / NLU
  • Predictive Analytics and Statistical Modeling
  • AI platform architecture and deployment
  • MLOps and model lifecycle governance
• Proven success leading large, complex, and multi-client AI/ML engagements in healthcare, life sciences, or closely related regulated industries
• Proven solid programming and technical leadership capabilities with technologies such as …