The candidate should have hands-on experience working with classic statistics, classic AI/ML approaches, and generative AI frameworks including their optimization; deploying AI models in production environments; leading development with teams leveraging a range of programming languages (e.g., Python, R, Java), AI tools (e.g., TensorFlow, PyTorch, scikit-learn) and associated enabling technologies including familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud). The Technical Manager will work in close partnership with internal IT stakeholders (architecture, applications, infrastructure analytics, IT operations, informatics), business partners (operations, clinical or shared business services), and external partners (vendors, academic or others) to accomplish program goals for AI, Automation, and AI governance.