AI Data Scientist Team Lead

Solution Architecture

• Design scalable AI architectures spanning batch and real-time workloads, ensuring solutions are production-grade, maintainable, and aligned with organizational priorities
• Gather and refine requirements from clinical informaticists, data scientists, and business stakeholders; translate complex needs into actionable technical specifications
• Architect agentic AI systems, RAG pipelines, and multi-model orchestration frameworks across clinical and operational domains
• Serve as technical authority on end-to-end AI pipeline design across Databricks, cloud-native platforms, and Epic integration points
• Drive build-vs-buy and technology selection decisions for emerging AI capabilities (generative AI, foundation models, LLM applications)
• Ensure AI systems adhere to healthcare security standards (HIPAA), AI governance frameworks, and responsible AI principles
• Partner with data architects and governance teams to enforce data quality, lineage, and access controls across AI data assets

Engineering Management

• Lead multiple concurrent AI projects; manage scope, timelines, and technical risk while removing obstacles for the team
• Mentor and develop 4 direct-report engineers; provide technical leadership and formal performance input for 3 matrixed engineers
• Establish platform engineering best practices, conduct architecture reviews, and foster engineering excellence across the full team
• Align technical execution with strategic goals; contribute data-driven insights to inform organizational AI initiatives
• Coordinate cross-functional collaboration between the AI Platform team and data scientists, software engineers, clinical informaticists, and business stakeholders
• Champion scalable and governed AI practices across the organization
• Run team rituals (daily standups, weekly planning, architecture office hours, biweekly demos, monthly capability health reviews, quarterly roadmap refresh)

Required Skills & Qualifications

• 8+ years in data science, ML engineering, or AI solution architecture, with at least 3 years in a technical leadership or engineering management role
• Demonstrated experience designing production ML/AI systems end-to-end: from data ingestion through model serving and monitoring
• Strong fluency in Python and SQL; hands-on experience with Databricks (MLflow, Unity Catalog, Spark) and cloud-native ML infrastructure (AWS preferred)
• Experience architecting agentic AI systems, LLM applications, or RAG pipelines in production settings
• Proven ability to translate ambiguous business problems into technical specifications and actionable engineering plans
• Track record of mentoring engineers across multiple specialties and managing concurrent technical projects
• Familiarity with healthcare data standards (HL7/FHIR) and regulatory requirements (HIPAA) strongly preferred
• Experience with Epic integration points (FHIR, SDE) a plus
• MS or PhD in Computer Science, Data Science, or related quantitative field preferred; equivalent experience accepted