Data and AI Engineer

The University of Michigan is a leading academic institution in the field of healthcare and research. They are seeking a full-time Data and AI Engineer to design, build, and maintain systems that support AI-driven research and clinical tools, working closely with various teams to ensure effective integration and compliance.

Responsibilities:

• Design, build, and maintain data pipelines and AI systems that support research and clinical workflows across AI&DHI initiatives
• Develop and manage containerized applications and services using Kubernetes (OpenShift), ensuring reliable, scalable deployment in secure research environments
• Integrate AI tools and research platforms with institutional systems including MiChart, ChatGPT/Claude, REDCap, and other Michigan Medicine infrastructure
• Architect and maintain backend systems that power AI-enabled research tools, including PRISM and HELPR LLM Tools
• Partner with researchers, clinicians, and technical teams to translate requirements into well-engineered, production-ready systems
• Ensure systems meet institutional security, compliance, and data governance standards, including HIPAA requirements for health data
• Develop clear technical documentation for all systems, pipelines, and integrations

Requirements:

• Master's degree in Computer Science, Data Engineering, Biomedical Informatics, or a related field
• 5 to 7 years of systems/software programming activities in a business environment with a comprehensive knowledge of software applications
• Experience working with EHR platforms, particularly Epic/MiChart integrations
• Familiarity with large language model (LLM) APIs and AI tool deployment
• Experience with Linux/Unix environments for research computing
• Experience working with sensitive and confidential data regulated by HIPAA
• Familiarity with HL7 FHIR standards for health data interoperability
• Bachelor's degree in Computer Science, Software Engineering, a related field, or equivalent experience
• 3-5 years of experience developing and deploying AI tools and systems
• Hands-on experience with Kubernetes (OpenShift) for container orchestration and deployment
• Proficiency in Python or equivalent languages for data engineering and systems development
• Experience with cloud-native infrastructure and DevOps practices, including CI/CD pipelines and version control (Git)
• Experience integrating software systems with external APIs and enterprise platforms
• Strong communication skills, both oral and written, with the ability to work across technical and non-technical teams
• Strong organizational skills with attention to detail and accuracy