Edtech.com's Summary

University of Michigan is hiring an Applied AI Engineer for a one-year post-graduate fellowship at the Center for Academic Innovation, focused on practical AI prototyping and platform operations. The engineer builds and tests AI-enabled workflows for Center projects and helps run a dedicated multi-GPU local AI server. Fellows also share their work through demonstrations, office hours, and workshops, and hand their documented projects to the next cohort.

Highlights

Prototype and test AI-enabled workflows for projects chosen through intake, building lightweight applications, connectors, retrieval pipelines, and automations that fit into existing Center systems.
Support pilots alongside domain experts by collecting user feedback, diagnosing failures, and iterating on fixes.
Build evaluation datasets, test cases, and repeatable harnesses that measure quality, reliability, safety, and cost.
Implement logging, access controls, guardrails, and operational telemetry in partnership with Technology Infrastructure and Support staff.
Operate the Center's multi-GPU local AI server and its open-source software stack, covering model deployment, updates, monitoring, and runbook upkeep.
Requires a bachelor's degree in computer science, information, data science, engineering, learning sciences, or a related field, or equivalent education and applied experience.
Needs hands-on programming experience in Python, JavaScript, or a similar language, including work with APIs, Git, and cloud or container environments.
Needs experience building with large language models, retrieval-augmented generation, structured outputs, or agents, and designing evaluations of the results.
The posted salary range is $85,000 to $92,000 per year.
Work in the office at least four days a week, Monday through Thursday, with remote work available on Fridays.

Applied AI Engineer Full Description

Who We Are

About the Center for Academic Innovation

Through curricular innovation, tools for student success, and educational research and analytics, the University of Michigan Center for Academic Innovation is building the future of education. Our vision is a future in which education connects and empowers learners everywhere to reach their full potential throughout their lives. To realize our vision, we make it our mission to collaborate across campus and around the world to create equitable, lifelong educational opportunities for learners everywhere.

About the Technology Infrastructure and Support Team

The TIS team builds and maintains the technology behind CAI's learning, media, and IT work. Our work spans Michigan Online infrastructure, cloud storage, cybersecurity, disaster recovery, studio production, XR, AV systems, media asset management, and internal support. TIS is also home to the AI Enablement Team, which partners with teams across the Center to test promising ideas and turn the ones that work into tools and workflows people can rely on. Working closely with Creative Studios, Operations, and product engineering teams, we keep CAI's systems dependable and secure so learners, faculty, and staff can focus on their work.

Responsibilities*

Prototype and test AI-enabled workflows for CAI projects selected through intake, building lightweight applications, connectors, retrieval pipelines, and automations that integrate with existing CAI systems
Support pilots with domain experts, collect user feedback, diagnose failures, and iterate
Build evaluation datasets, test cases, and repeatable harnesses for quality, reliability, safety, and cost
Implement logging, access controls, guardrails, and operational telemetry in partnership with TIS staff
Establish defined operating work for CAI's local AI server, including model deployment, updates, monitoring, and runbook upkeep
Share practical guidance through demonstrations, office hours, and workshops for staff and student fellows

What You'll Do

The Center for Academic Innovation at the University of Michigan is seeking an Applied AI Engineer for a one-year post-graduate fellowship focused on practical AI prototyping, evaluation, platform operations, and knowledge transfer. Reporting to the Director of Technology Infrastructure and Support, you will work closely with the AI Enablement Lead and TIS colleagues to build and test AI-enabled workflows, integrations, evaluation tools, and technical documentation. The successful candidate is a careful builder who can learn quickly, explain tradeoffs clearly, and turn experiments into maintainable, well-documented assets.

What makes this fellowship distinctive

You will help operate CAI's dedicated multi-GPU local AI server and the open-source software stack that supports it, gaining experience deploying, evaluating, and monitoring models. Projects across the Center will give you a varied portfolio of applications and reusable tools. You will also share your work through demonstrations, office hours, and workshops. The fellowship combines hands-on delivery, platform operations, and knowledge transfer, with documented project outcomes and a handoff to the next cohort to help build a fellowship alumni community over time.

Required Qualifications*

A bachelor's degree in computer science, information, human-computer interaction, data science, engineering, learning sciences, or a related field, or an equivalent combination of education and applied experience, completed by the start date
Hands-on programming experience in Python, JavaScript, or a comparable language, including experience working with APIs
Experience building applications with large language models, retrieval-augmented generation, structured outputs, agents, or related AI techniques
Experience using Git and working with cloud, container, or modern application-development environments
Experience designing tests or evaluations and interpreting both quantitative results and user feedback
Working knowledge of software security, privacy, access control, and responsible AI practices
Experience with retrieval-augmented generation and agent frameworks, experience with evaluation or observability tooling
Ability to learn and appropriately use new technologies to improve processes, communication, and outcomes, including AI-enabled tools where relevant to the role, consistent with university policy and job responsibilities

Additional Information

This is a one-year term-limited fellowship with the possibility of annual renewal depending on funding and performance.

Candidates must have legal authorization to work in the United States.

The mode of work for this position is Hybrid with a minimum of 4 days in the office per week, Monday through Thursday, with an option of remote work on Fridays. On occasion, you may be required and must be available to work onsite on Fridays if necessitated by our center's policy and domain leadership or by your job requirements.

The salary for this position will be based upon the selected candidate's education and experience.

Salary Information

The general salary range for this position is $85,000 - $92,000. Candidates can expect to be paid a competitive and equitable salary. Factors used to determine salary include education level, experience, knowledge and skills for the position and salaries that are currently established within the unit. All candidates are encouraged to discuss salary questions to honor alignment and transparency throughout the recruiting process.

Background Screening

The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks. Background checks will be performed in compliance with the Fair Credit Reporting Act.

U-M EEO Statement

The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.

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