AI Data Scientist Team Lead

Job Description

Job Summary The AI Data Scientist Team Lead (Manager, AI Platform Engineering) architects end-to-end AI solutions and leads the AI Platform team for Geisinger’s AI Department. This is a hands-on technical leadership role, splitting time equally between solution architecture and engineering management (50% technical / 50% leadership). On the technical side, the Team Lead serves as the solution architect across the AI Platform portfolio: gathering requirements from clinical informaticists, data scientists, and business stakeholders; designing production-grade AI architectures spanning batch and real-time workloads; and making build-vs-buy calls for emerging AI capabilities. On the management side, the Team Lead runs the team’s rituals, removes blockers, develops direct reports, and manages stakeholder expectations. The AI Platform team is an enabling team-not a delivery team-that builds the reusable capabilities, tooling, and infrastructure that let product teams deploy AI safely and quickly. The team consists of 8 engineers supporting 10 platform capabilities across 70 AI programs. The Team Lead owns the team’s capability roadmap, capacity allocation, platform engineering standards, and architecture reviews, while translating organizational AI strategy into executable technical plans that deliver production-grade capabilities across the portfolio. Job Duties ​What You Will Own: Solution architecture across all platform capabilities (agentic AI systems, RAG pipelines, multi-model orchestration, real-time and batch ML infrastructure) Requirements gathering and technical specification for AI programs across clinical and operational domains Build-vs-buy and technology selection decisions for emerging AI capabilities, including generative AI, foundation models, and LLM applications Platform engineering standards, architecture reviews, and governance compliance (HIPAA, AI risk management, responsible AI principles)