Join Optum, a global health optimization leader, and leverage technology to improve millions of lives. Our inclusive culture fosters collaboration with talented peers, offering comprehensive benefits and career growth. You'll connect people with essential care, pharmacy benefits, data, and resources, making a significant impact on communities worldwide. We are dedicated to advancing health optimization and invite you to start Caring. Connecting. Growing together.

This Senior Manager role focuses on leading AI/ML Engineering within a dynamic environment, driving innovation and delivering scalable solutions.

Lead the design, development, and deployment of cutting-edge machine learning and Generative AI solutions for clinical, pharmacy, and operational use cases. Build advanced predictive models, recommendation systems, NLP solutions, deep learning architectures, and LLM-powered applications. Optimize data pipelines, feature engineering, and model training frameworks using extensive healthcare and business datasets. Implement Retrieval-Augmented Generation (RAG) architectures, vector search, prompt engineering, and LLM evaluation strategies. Fine-tune and deploy foundation models, ensuring high levels of reliability, scalability, security, and performance. Drive MLOps and LLMOps best practices, including CI/CD, automated testing, monitoring, and observability. Collaborate with cross-functional teams to translate business needs into robust AI solutions. Uphold Responsible AI principles, data governance, HIPAA compliance, and enterprise security standards. Analyze and enhance model performance, focusing on accuracy, latency, cost, and user experience. Provide technical leadership, mentor junior engineers, and contribute to best practices. Evaluate emerging AI technologies and their potential business value. Support production AI systems through monitoring and issue resolution.

A Bachelor's degree in a relevant technical field such as Computer Science, Engineering, or Data Science is required, alongside over 15 years of comprehensive technology experience. This includes a strong background in software engineering, application development, or enterprise solution delivery, with at least 5 years of hands-on Python and SQL programming. Proven expertise in designing and developing scalable, reliable, and secure enterprise-grade software solutions is essential. Experience with modern application development frameworks, REST APIs, microservices, Docker, CI/CD practices, and cloud platforms (Azure, AWS, GCP) is crucial. Solid understanding of data engineering, analytics concepts, and production engineering considerations, including monitoring and observability, is expected. Excellent analytical, problem-solving, communication, and stakeholder management skills are necessary. The ability to provide technical leadership, conduct design and code reviews, and mentor engineers is a key requirement.