Sr Director AI or ML Engineering Remote Nationwide or Hybrid in MN, DC

UnitedHealth Group•Eden Prairie, MN

1d•$203,200 - $348,400•Hybrid

About The Position

Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care’s most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together. As the Senior Director of AI/ML Engineering (Forward Deployed Engineering Sr Director) for Optum Health Technology, you will lead the charge in transforming cutting-edge artificial intelligence proofs-of-concept into robust, production-grade enterprise systems. In this highly strategic yet hands-on role, you will embed with client and lead the engineering teams to deploy advanced AI solutions, optimize Large Language Models (LLMs), and build agentic workflows that drive efficiency and improve delivery across Optum Health. You will lead the design, development, and scale AI-driven SaaS solutions, leveraging modern cloud platforms (AWS, Azure, and GCP) and state-of-the-art machine learning libraries. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

Requirements

Bachelor’s degree or equivalent experience (e.g., 4+ years of additional experience in software or systems engineering in lieu of a degree)
10+ years of experience with a progressive career path leading to technical leadership or director-level roles
8+ years of experience developing and deploying enterprise-scale software solutions or AI/ML SaaS products in production environments
5+ years of hands-on programming experience with languages such as Python or Bash, and machine learning libraries/frameworks
3+ years of experience with public cloud platforms (e.g., AWS, Azure, and/or GCP) for AI/ML model deployment and infrastructure management
3+ years of experience implementing statistical methods, data pipelines, and machine learning algorithms
Experience establishing system performance KPIs and implementing model monitoring, fairness, and bias mitigation techniques

Nice To Haves

Master's degree or PhD in Computer Science, Machine Learning, AI, or a related technical field
Direct, active technical expertise in Natural Language Processing (NLP), Large Language Models (LLMs), retrieval-augmented generation (RAG), and agentic workflows
Experience designing and deploying AI solutions within the healthcare domain or a highly regulated industry
Experience designing security and compliance standards for AI models handling sensitive data (e.g., PHI or HIPAA-regulated data)
Demonstrated solid communication, executive presence, and stakeholder management skills, with a proven ability to present technical strategies to C-level executives

Responsibilities

Develop and execute org-wide AI strategy and roadmap aligned with business objectives and growth initiatives, presenting the vision, roadmaps, and results to executive leadership
Lead enterprise AI engineering, deployment, and operations, transforming AI proofs-of-concept into robust, production-grade systems that deliver real business value
Strategically use AI to solve problems, unlock opportunities, and deliver tangible business value, championing AI as a core driver of the team's success and proactively shaping how it is developed, deployed, and utilized
Integrate enterprise AI tools, set AI goals in development plans, and align hiring with AI competencies, actively removing barriers to accelerate adoption
Champion the ethical use of AI by embedding transparency, fairness, and accountability throughout the entire AI lifecycle, ensuring AI solutions are compliant with standards and client requirements
Spearhead the design and deployment of AI models (including statistical analysis, deep learning, LLMs, and agentic workflows), data pipelines, and retrieval frameworks
Foster deep collaboration with engineering and client teams to integrate AI solutions with existing systems, customize solutions, and provide technical support and guidance
Monitor AI system performance, scalability, reliability, and cost-effectiveness, establishing KPIs and driving continuous optimization
Mentor, develop, and retain top AI talent while building a culture of innovation and documenting best practices into reusable playbooks