AI Data Scientist Team Lead

Geisinger

23h•Remote

About The Position

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 across 6 distinct roles (4 direct reports + 3 matrixed engineers from partner departments), currently supporting 10 platform capabilities serving 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.

Requirements

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
Bachelor's Degree- (Required)
Minimum of 6 years-Relevant experience (Required)
Analyzing, processing and building AI/ML solutions from Clinical and Operational data sources, such as Epic Clarity, HL7, DICOM, or ECG data, Clinical Databases, Communication, Critical Thinking, Data Analysis, Data Presentations, Group Collaboration, Leadership, Machine Learning Methods, Programming Languages, Structured Query Language (SQL)

Nice To Haves

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

Responsibilities

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)
Team roadmap, capacity allocation, and intake triage for platform support requests
People management, career development, and performance evaluation for 4 direct reports (3 MLOps Engineers, 1 Full Stack Engineer)
Work direction, priorities, platform standards, and formal performance input for 3 matrixed engineers from partner departments (Sr. Platform Data Engineer, Sr. Software Engineer for Integration & Interfaces, Sr. Platform Engineer)
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
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)

Benefits

We offer healthcare benefits for full time and part time positions from day one, including vision, dental and domestic partners.
Perhaps just as important, we encourage an atmosphere of collaboration, cooperation and collegiality.
We know that a diverse workforce with unique experiences and backgrounds makes our team stronger.

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