Director AI or 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:

• Champion the AI first modernization agenda, embedding AI/ML into enterprise workflows, products, and operations
• Partner with business leaders to identify high impact AI use cases, assess feasibility, and define value realization frameworks
• Translate business goals into a prioritized AI portfolio, ensuring measurable outcomes and alignment with enterprise strategy
• Lead the design, development, and deployment of scalable AI/ML, GenAI, LLM, RAG, and Agentic AI systems
• Build AI products using modern ML architectures, vector stores, multimodal models, and model orchestration frameworks
• Oversee the end to end lifecycle - from problem definition → experimentation → model development → evaluation → deployment → monitoring
• Guide teams on best practices for healthcare AI, including clinical validation, data quality, safety, and regulatory alignment
• Implement ethical AI frameworks, including bias detection, explainability, transparency, and governance standards
• Provide solid technical leadership in ML engineering, model optimization, scalable model deployment, and distributed training
• Mentor and lead AI/ML engineers, data scientists, and applied researchers
• Build a culture of innovation, experimentation, engineering excellence, and continuous learning
• Champion the organization's MLOps strategy, driving automation, reproducibility, CI/CD for ML, model versioning, monitoring, and governance
• Partner with cloud/platform teams to implement robust, secure, and scalable AI infrastructure
• Ensure platform readiness for GenAI, LLMOps, prompt management, evaluation frameworks, and agent orchestration
• Collaborate with Product, Engineering, Cloud, Data, Security, Compliance, and Business stakeholders
• Promote solid alignment between AI CoE and enterprise technology teams
• 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:

• Extensive Leadership in Enterprise AI: 15+ years of progressive experience, with a significant track record of leading the development, deployment, and operationalization of high-impact AI/ML solutions within a large, complex enterprise
• Proven Expertise in AI Governance, Risk, and Compliance: Demonstrated experience designing or leading AI governance frameworks. Must have direct experience navigating internal review boards (like an AIRB), ensuring AI projects meet rigorous ethical, fairness, legal, and regulatory standards (e.g., HIPAA)
• Deep Generative AI & Machine Learning Expertise: Authoritative knowledge and hands-on implementation experience with Generative AI and LLMs, alongside a broad understanding of traditional ML algorithms (e.g., for OCR, Speech, Deep Learning)
• Strategic Business Acumen: Proven track record of developing and executing enterprise-wide AI strategy. Must be able to translate business goals into a technical roadmap and articulate the ROI and business value of AI initiatives to executive leadership
• Full ML Lifecycle & Productization Proficiency: Solid proficiency across the entire machine learning lifecycle with a product-centric mindset, including a demonstrated ability to guide teams in engineering robust, scalable, and maintainable AI products and platforms
• Exceptional Communication & Influence: Demonstrated world-class communication skills with the proven ability to influence and align cross-functional teams and senior leaders across business, legal, compliance, and technology domains

Preferred Qualifications:

• Advanced Degree: A Master's or Ph.D. in Computer Science, Artificial Intelligence, Data Science, or a related quantitative field
• Advanced MLOps & Cloud Architecture: Deep, hands-on experience designing and implementing sophisticated MLOps pipelines and scalable, cloud-native AI architectures on major platforms (AWS, Azure, or GCP)
• Deep Domain Expertise in Healthcare AI: Significant experience applying AI/ML specifically within the healthcare sector (e.g., claims processing, clinical decision support, patient engagement, call centre optimization)
• Thought Leadership: A recognized presence in the AI/ML community, demonstrated through publications, patents, conference presentations, or significant open-source contributions
• Change Management Experience: Demonstrated success in leading large-scale organizational change initiatives, specifically related to driving an 'AI-First' or data-driven culture
• Track Record of Building & Scaling Teams: Proven ability to attract, build, mentor, and retain high-performing, multi-disciplinary AI teams (including ML Engineers, Data Scientists, and Research Scientists)

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.