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

Primary 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

Required Qualifications

• 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

Preferred Qualifications

• 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