Join Optum's global organization, where technology drives health optimization for millions. This role is within a collaborative AI Platform team focused on building a payer-centric agentic platform. The platform orchestrates data, models, and workflows to enhance complex healthcare operations. You will provide essential onshore leadership for AI platform execution and deployment, ensuring secure and scalable delivery of reusable AI services.

Our team designs and deploys intelligent, agent-driven applications that analyze clinical and administrative data, evaluate AI outputs, and automate decision workflows. We ensure our production systems are reliable, scalable, and continuously improved.

By applying AI to agentic workflows, deployment automation, and production observability, you will accelerate delivery, reduce risk, and foster platform reuse. With vast data and resources, our solutions process millions of clinical data elements, benefiting millions of patients. We are a diverse, global team passionate about improving patient outcomes and streamlining healthcare payments.

Provide strategic and technical leadership for AI platform execution and deployment across Payment Integrity and Optum Real. Ensure secure, reliable, and scalable delivery of reusable AI services. Lead and inspire a high-performing team of AI/ML engineers, fostering a culture of trust and excellence. Champion AI as a core driver for success, strategically designing, developing, and deploying AI-powered solutions for complex healthcare challenges.

Design and deliver intelligent, agentic workflows and applications that analyze clinical and administrative data. Drive engineering and operational excellence through AI in deployment automation, testing, CI/CD, and production observability. Leverage enterprise AI tools to streamline workflows and automate tasks. Champion ethical AI practices, embedding transparency and accountability.

Partner cross-functionally with product managers, integration teams, and stakeholders to represent the engineering vision and accelerate platform reuse. Comply with all company policies and directives.

A Bachelor's degree or Master's in Computer Science, Software Engineering, IT, Mathematics, Statistics, or a related quantitative field, or 4+ years of equivalent software engineering experience is required. You should have 12+ years of experience in Software Engineering and Data Analytics, with at least 3 years focused on AI/ML engineering.

Minimum of 3 years managing, coaching, and developing engineering teams of 5+ people, including senior engineers, is essential. Experience with Generative AI technologies such as LLMs (OpenAI, Claude, Gemini), LangChain, AI Agents, RAG, Vector Databases, Prompt Engineering, and model fine-tuning is needed (2+ years hands-on).

Proficiency in DevSecOps, CI/CD practices (Git, Jenkins), and Python for data analysis and AI/ML development is crucial. Experience leading AI/ML projects from ideation to production delivery is expected. Technical experience with major cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes) is also required.