AI Engineer

GOLDEN GATE UNIVERSITY•San Francisco, CA

24d•$150,000 - $175,000•Remote

About The Position

Golden Gate University (GGU) is seeking an AI Engineer to support the redesign of its data infrastructure and reporting functions with AI at the core. This role is central to the university's future, which is being built around AI in both academic programs and institutional operations. The AI Engineer will partner with the university's executive leadership team to build AI tools and workflows that enhance the effectiveness and efficiency of reporting functions, including external agency reports and internal leadership reports. Additionally, the role involves building AI tools for data analysis in priority areas such as enrollment and financial projections, and designing AI tools to support other assigned leadership priorities in coordination with the Vice Provost for Digital Innovation.

Requirements

Demonstrated experience building LLM-based tools used in production, including agent workflows, retrieval, structured extraction, tool use, and evaluation.
Strong Python and solid SQL skills.
Sufficient data engineering experience to connect AI tools to institutional systems reliably.
A record of AI tools built, shipped, and maintained (candidates should be prepared to demonstrate one).
The ability to take a well-framed request from a non-technical leader and return a working tool, independently.
Excellent communication skills.
Ability to work effectively with senior leadership.

Nice To Haves

Experience in higher education.
Experience with Ellucian Colleague or another student information system.
Familiarity with FERPA.

Responsibilities

Build AI tools and workflows to automate data flows from the University’s student information system (Ellucian Colleague) and other core systems.
Enhance the speed and reliability of the University’s reports, including required reports to outside agencies and internal reports for leadership.
Own the AI stack for institutional reporting and analysis: choose models and platforms, design prompts and agents, test for reliability, and manage integrations and costs.
Build AI tools for analysis in areas of leadership priority, such as enrollment projections and financial projections.
Turn analyses framed in spreadsheets into durable, self-updating tools.
Design AI tools and workflows in other areas of the University as needs arise.
Advise leadership on the capabilities and limitations of AI tools in institutional operations and recommend areas for implementation.