• Develop and tune generative/agentic AI solutions aimed to solve highly complex problems within the delivery of healthcare or health plan services. • Establish comprehensive tracking of experiments to manage the iterative process of building and testing models ensuring that AI solutions fulfill business requirements. • Provide statistical rigor to these evaluations via the design of controlled tests to measure the impact of changes to the solution. • Form and leverage strong collaborations with AI engineers to scale solutions for production grade performance. • Develop and implement complex agentic workflows that utilize AI agents for autonomous task execution, enhancing operational efficiency and decision-making capabilities. • Solve new business problems by reaching, designing, building, and validating complex or novel machine learning models. • Conduct feature engineering and model optimization. • Manage the complete lifecycle of machine learning models from conception to deployment while following SDLC and responsible AI practices. • Consult with senior and executive level business leaders to scope, model, and recommend AI/ML, technical, or analytic solutions to highly complex problems within healthcare. • Build and ensure consensus with stakeholders regarding the feasibility, tradeoffs, and delivery of recommended solutions. • Research, recommend, and apply causal techniques (RCT, DiD, PSM, causal graph models, counterfactual reasoning, etc.) to estimate treatment effects to quantify or validate business benefit of complex health plan activities. • Explain business impact to program owners and leadership using approaches that are meaningful to those audiences. • Partner with program owner in the promotion or publications of results when applicable. • Participate in code peer reviews and quality assurance testing. • Troubleshoot issues as they arise to solve problems independently and collaboratively. • Serve as the technical subject matter expert to establish best practices for the team and help coach the team via formal and informal initiatives. • Maintain regular contact with customers through development cycle to ensure each step of implementation tracks customer’s needs. • Lead analytics projects applying a working knowledge of Agile and SCRUM project methodologies.