AI Solutions Developer

provide support to our researchers to realize our vision of research to serve the world. OVPR runs on systems that were never designed to talk to each other. Our small IT team supports more than thirty units, and much of what we build closes that gap: pulling identity, human resources, finance, space, and service data into one place, then replacing manual, spreadsheet driven work with software people actually want to use. In this role you will design and build those applications. You will write the code, own the data structures behind it, and integrate against university services through the U-M API Gateway and central identity systems. You will also sit with the staff whose process you are automating and ask enough questions to understand it before you build anything. And you will use AI as an engineering tool rather than a talking point, because a growing share of what we ship is built with, or powered by, the university's generative AI platforms. This is a small team with a wide surface. You will own work early, you will see it in production quickly, and the people using it are the ones supporting research across the university. Application Development and Integration Design, build, and maintain web applications and internal tools that consolidate data from across the university, including OVPR's Backstage portal and its custom plugins. Develop and consume APIs, including university services reached through the U-M API Gateway such as Finance, Department, MCommunity, and TeamDynamix. Integrate applications with central identity services including Okta OIDC and Shibboleth, and with unit systems of record such as CollectionSpace. Deploy and support containerized applications on the U-M Container Service. Troubleshoot and resolve defects across the full stack, from the interface through to the data layer. Data Architecture and Management Model, build, and query the relational data behind OVPR applications, keeping structures clear enough that a small team can maintain them. Aggregate data across sources that frequently disagree, including identity claims, human resources records, financial shortcodes, space and equipment data, and group memberships. Build reporting and dashboards that answer the questions OVPR units ask repeatedly. Apply appropriate handling for institutional data based on its sensitivity classification. Process Automation and Applied AI Turn documented business processes into working automation, replacing manual and spreadsheet based workflows with supported applications. Apply the university's generative AI platforms, including the U-M GPT Toolkit and ITS AI Workflows, to automate multi step work with human review built in. Evaluate where AI genuinely improves an outcome and where a conventional solution is the better answer. Identify automation opportunities while working alongside unit staff, and raise them rather than waiting to be asked. Requirements and Collaboration Work directly with OVPR unit staff to understand how a process actually runs, not only how it is documented, and translate that into a technical design. Partner with ITS and other technical providers on shared services, integrations, and dependencies. Explain technical tradeoffs clearly to people without a technical background, and bring them along on the decision. Coordinate with the IT Business Consultant and Associate Director so that consultation, project delivery, and development stay aligned. Technical Practice and Documentation Document applications, data structures, and integrations so that a small team can support them over time. Contribute to code review, shared standards, and OVPR's version control practice. Build and maintain applications in line with web accessibility standards and the university's obligations. Stay current on university services and emerging technology, and bring back what is worth adopting. Bachelor's Degree or Equivalent Experience: A bachelor's degree in computer science, information systems, information technology, or a related field, or an equivalent combination of education, certification, and experience that demonstrates the foundational knowledge required for this role. Application Development Experience: Two or more years of professional experience building and maintaining web applications, including both interface and server side work, and delivering them to real users. Database and Data Structure Proficiency: Demonstrated experience with relational databases, including schema design, writing non trivial queries, and reasoning about how data should be structured rather than only consuming it. Systems Integration and APIs: Hands on experience consuming and building REST APIs, and connecting systems that were not designed to work together, including handling authentication, error conditions, and inconsistent data. Programming Proficiency: Working proficiency in at least one server side language such as PHP, Python, or JavaScript, with the ability to read and extend an unfamiliar codebase. Collaborative Development Practice: Experience with version control and collaborative development, such as Git and review based workflows. Communication and Requirements Gathering: Ability to explain technical work clearly to people who are not technical, and to gather requirements by asking questions that surface what was left unsaid. Independent Learning: Demonstrated ability to learn unfamiliar technologies quickly and with limited direction. University and Enterprise Systems Experience: Experience working within a university or another large, decentralized enterprise environment, with a working understanding of how central services, unit level systems, and institutional policy fit together, and why the same information often lives in several systems at once. Familiarity with University of Michigan Services: Exposure to U-M systems and services such as the U-M API Gateway, Okta and Shibboleth, MCommunity, TeamDynamix, M-Pathways, or the U-M Container Service. Applied Generative AI: Experience putting generative AI into production, including large language model APIs, retrieval over institutional content, or agentic workflows, together with sound judgment about where AI belongs and where it does not. Enterprise AI Platforms: Experience with the U-M GPT Toolkit, ITS AI Workflows, or comparable enterprise AI platforms and their data handling requirements. Business Process Analysis: Experience documenting, analyzing, and improving business processes, and comfort leading that conversation with the people who own the process. Higher Education or Research Context: Experience in higher education, research administration, or another environment with meaningful compliance and policy requirements. Accessibility Awareness: Working knowledge of web accessibility standards, including WCAG conformance and ADA Title II obligations. Platform and Infrastructure Breadth: Experience with WordPress development, containerization, or infrastructure as code. Institutional Awareness and Influence: Ability to move work forward across unit boundaries without formal authority, and awareness of how institutional politics shape what is actually possible. 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 are performed in compliance with the Fair Credit Reporting Act. Job openings are posted for a minimum of seven calendar days. The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled any time after the minimum posting period has ended. 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.