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

Define and lead the enterprise Data & AI Platform Strategy, ensuring scalable, secure, resilient, and cost-efficient platforms for Analytics, ML, GenAI, and Agentic AI

Build AI-ready data foundations using semantic layers, metadata management, data lineage, knowledge graphs, and governance frameworks

Lead data engineering teams responsible for ingestion, transformation, storage, pipelines, APIs, data products, and real-time data solutions

Establish engineering standards, reusable frameworks, and drive modernization of legacy systems into cloud-native architectures

Partner with Data Science and AI teams to operationalize ML, GenAI, and Agentic AI solutions

Enable capabilities such as feature stores, vector databases, embeddings, RAG, model deployment, monitoring, observability, explainability, and Responsible AI

Drive enterprise-wide data governance, including data quality, stewardship, cataloging, lineage, master data management, privacy, and compliance

Govern both AI training datasets and AI-generated outputs

Promote a Data-as-a-Product operating model with defined ownership, SLAs, and quality standards

Prioritize platform and data initiatives based on business value, AI readiness, and measurable outcomes

Evaluate and implement emerging technologies including GenAI, Agentic AI, Data Fabric, Semantic Layers, Knowledge Graphs, and Intelligent Automation

Lead proofs of concept and scale successful innovations across the enterprise

Partner with business, product, analytics, and technology leaders to align platform investments with strategic objectives

Present technology strategy and roadmap recommendations to executive leadership

Manage budgets, vendors, cloud spend, operational performance, and platform reliability

Establish KPIs for performance, availability, productivity, automation, and cost optimization

Build, mentor, and develop high-performing Data & AI engineering teams

Foster innovation, accountability, continuous learning, talent development, and career growth

Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements

Required Qualifications

Extensive leadership experience in Data Engineering, Data Platforms, AI/ML Platforms, or Enterprise Data Architecture

Experience implementing Data-as-a-Product frameworks and enterprise data strategies

Experience managing large-scale engineering organizations, budgets, vendors, and cloud cost optimization initiatives

Solid expertise in cloud-based data ecosystems and modern data platform architectures

Deep knowledge of data engineering concepts including data pipelines, APIs, data products, streaming, and real-time processing

Hands-on understanding of AI/ML operationalization, including

MLOps

GenAI

Agentic AI

Vector Databases

RAG (Retrieval-Augmented Generation)

Embeddings

Model Deployment & Monitoring

Responsible AI

Solid understanding of enterprise data governance, data quality, lineage, metadata management, cataloging, MDM, privacy, and regulatory compliance

Knowledge of emerging technologies such as

GenAI

Agentic AI

Data Fabric

Knowledge Graphs

Semantic Layers

Intelligent Automation

Solid stakeholder management and executive communication skills

Proven ability to build and lead high-performing teams across data engineering, analytics, governance, and AI domains

Demonstrated success in driving platform modernization, digital transformation, and enterprise-scale technology adoption

Success Metrics

Data quality and reliability

AI adoption and business impact

Platform availability and performance

Data product adoption

Engineering productivity and automation

Cloud cost optimization

Regulatory compliance

Team engagement and retention

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.