A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.
We're hiring a full-time Data and AI Engineer to design, build, and maintain the data systems, pipelines, and AI integrations that power research and clinical tools across Michigan Medicine. This role centers on data architecture, EHR data integration, database engineering, and technical consultation, with additional contributions to backend development, APIs, automation, and AI systems integration.
You'll sit at the intersection of data engineering and applied AI ? building robust, production-grade data pipelines, managing OpenShift/Kubernetes-based infrastructure, and integrating AI tools with platforms including Epic EHR, frontier and enterprise LLMs, and other services across the university. We're looking for a self-motivated engineer with strong experience in data systems development, container orchestration, and AI tool deployment who thrives in a collaborative, research-driven environment and enjoys solving complex technical problems that directly impact clinical and research outcomes.
This position is hybrid, based primarily from home with onsite opportunities in Ann Arbor, Michigan. A fully remote arrangement will be considered for exceptional candidates.
- Serve as a primary technical resource for understanding and interpreting Michigan Medicine EHR data across a broad range of clinical, operational, and research domains.
- Develop and maintain a detailed understanding of how Epic MiChart data is created, represented, integrated, and made available through systems such as Clarity, Caboodle, Chronicles, FHIR services, HL7 interfaces, and institutional data warehouses.
- Investigate unfamiliar clinical, nursing, hospital, and administrative workflows to determine how the underlying data should be interpreted and used.
- Design, build, and support real-time and batch healthcare-data integrations, including HL7 ADT, radiology, cardiology, laboratory, and other clinical interface feeds.
- Work with institutional integration technologies and teams, including interface engines and messaging infrastructure, to ingest, transform, validate, and deliver clinical data.
- Serve as a data consultant to researchers, clinicians, analysts, and software engineers by helping them identify appropriate data sources, understand data limitations, and design effective data-driven solutions.
- Independently research complex data questions while recognizing when clinical, operational, Epic, or infrastructure subject-matter experts should be engaged to validate assumptions and conclusions.
-
