Optum is seeking a Senior Director of Software & AI/ML Engineering for GTS. This pivotal role involves shaping the strategic vision and architectural direction for scalable, resilient, and secure software and AI/ML solutions within healthcare applications. You will lead teams in delivering cloud-native services, robust APIs, and advanced AI/ML capabilities including generative AI and AI agents for workflow automation and decision support. The position emphasizes advancing AI-powered development tools and establishing rigorous engineering standards for evaluation, deployment, and monitoring, all while upholding responsible AI practices.

This leadership role encompasses people management, talent development, and team performance, requiring close collaboration with product, data, security, and business leaders. You will be instrumental in developing engineering leaders, guiding critical architectural decisions, and accelerating both software modernization and AI adoption. While maintaining technical depth through reviews and prototypes, the focus is on strategic leadership rather than hands-on individual contribution.

Define engineering strategy, roadmaps, and delivery standards, prioritizing the AI/ML portfolio with business partners to balance value, risk, and technical debt. Lead and manage software and AI/ML teams, setting clear goals, providing regular coaching, conducting performance reviews, and supporting career development. Oversee hiring, workforce planning, skills development, and succession planning, focusing on building a culture of accountability and continuous learning. Manage multi-team delivery commitments, resource allocation, and engineering budgets, including cloud and AI service costs. Guide architecture for scalable, resilient, and secure cloud-native services, APIs, data integrations, and reusable platforms. Lead applied ML, generative AI, RAG, AI agents, and cloud AI services, ensuring alignment with business needs and measurable benefits. Establish rigorous evaluation standards for large language models (LLMs) and other models, requiring comprehensive testing before release. Implement robust MLOps and LLMOps practices for automated evaluation, deployment, monitoring, and rollback. Integrate responsible AI, security, and privacy into the design and delivery processes. Enhance coding, testing, and CI/CD practices to ensure production readiness and service reliability. Drive the adoption of reusable components and AI-powered development tools, measuring and scaling their business impact.

A Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience, is required. Possess at least 18 years of relevant engineering experience, including significant delivery of production software and cloud-based systems. Demonstrate over 7 years of people leadership experience, encompassing direct management, hiring, performance management, and career development. Have at least 5 years of experience leading production AI/ML initiatives, with accountability for model evaluation, deployment, and business outcomes. Proven ability to set engineering roadmaps, manage capacity and costs, and make portfolio trade-offs. Exhibit a strong technical foundation in backend engineering, distributed systems, APIs, cloud architecture, and secure delivery, with proficiency in a backend language and Python. Possess a proven ability to influence senior stakeholders and collaborate effectively across product, data, security, and operations teams. Strong communication skills are essential for clearly articulating technical risks and leading teams through change.