Director - AI/ML Engineering - Hybrid in Minnetonka, MN

UnitedHealth Group•Minnetonka, MN

4h•Hybrid

About The Position

Optum Tech is a global leader in health care innovation, developing cutting-edge solutions in advanced data analytics, AI, and cybersecurity to improve health care. The Director, Applied AI & Data Science is a hands-on technology delivery leader responsible for identifying, shaping, and delivering AI-driven transformations across the MedicareIQ program. This role involves partnering with business leaders to uncover high-impact opportunities where AI (Data Science, Machine learning, and Agentic AI) can improve cost, operational efficiency, and member outcomes, translating these into funded, enterprise-scale initiatives. The leader curates and prioritizes a portfolio of AI use cases, defines value propositions and success metrics, and builds executive-ready proposals. The position requires strong leadership presence to influence investment decisions, secure funding, and champion initiatives from concept through approval and scaled delivery. This position follows a hybrid schedule with four in-office days per week.

Requirements

12+ years of experience in the IT industry with Master’s degree in Statistics, Computer Science, Mathematics, Data Science, or a related discipline
5+ years of enterprise leadership experience defining strategy, architecture, and delivery across multiple teams
3+ years of experience leading largescale applied AI/ML engineering organizations (20–50+ team consisting of engineers, data scientists, and ML engineers, across shores) delivering end-to-end production-grade software platforms
Proven success with building and operating AI enabled software products—from full stack application development to AI/ML integrated solution—with multi-million-dollar annual budgets in healthcare or similarly regulated environments
Demonstrated solid business acumen with ability to link AI investments to ROI, risk, and strategic outcomes
Demonstrated executive communication skills and ability to influence funding and prioritization decisions

Nice To Haves

Proven deep domain expertise in healthcare and regulatory frameworks
Demonstrated success in scaling GenAI and enterprise-grade ML capabilities across large enterprises
Proven solid understanding of Medicare regulatory needs including data governance, privacy, and HIPAA compliance
Proficiency in solving combinatorial optimization challenges through AI, and integrating them into mainstream solutions

Responsibilities

Drive end-to-end AI enabled software delivery aligned to business transformation with measurable outcomes within MedicareIQ program
Partners with business leaders to identify and shape high impact opportunities where AI can drive transformative outcomes. Develops executive ready use cases with clear value propositions and presents them to senior leadership to secure alignment and funding
Own end-to-end lifecycle delivery of Software Engineering — from problem framing and design through development, deployment, scaling, and optimization of production grade Data Science, Machine learning and Agentic AI solutions
Provide technical leadership ensuring scalable, secure, and resilient production-ready systems
Embed responsible and secure AI practices across the delivery lifecycle, including governance, fairness, transparency, compliance, and adherence while adhering to enterprise security standards
Build and lead high performing greenfield AI engineering team, fostering a culture of innovation, continuous learning, team mentorship and engineering excellence
Partner cross-functionally across product, finance, compliance, infrastructure, security, and business leaders to deliver integrated, enterprise-aligned AI solutions
Communicate AI purpose, delivery progress, and business impact with clarity and executive presence to senior leadership