Number of Positions: 1
Position Available: August 16, 2026
Position Title: Library Automation and AI Systems GRA
Department: Content Management, UT Libraries
Supervisor: Kay Ishola
The University of Texas Libraries advances teaching, catalyzes research, and democratizes learning in order to develop critical thinkers and global citizens. As an essential campus partner in building a rich research and learning ecosystem, we are committed to creating and sustaining a community that welcomes and respects all individuals, celebrates different perspectives and experiences, and fosters belonging. To learn more about UT Libraries, please visit our website: https://www.lib.utexas.edu/
Position is subject to renewal each semester.
This is a high-impact, research-forward role for a graduate student ready to build real systems at the intersection of artificial intelligence, library automation, and information science. The Library Automation and AI Systems GRA will work directly with the Automation and Integration Librarian to design, develop, and deploy AI-assisted tools and workflows that are transforming how the University of Texas Libraries catalogs, manages, and provides access to its collections.
This is not a traditional GRA role. You will write production code, contribute to peer-reviewed research, present at conferences, and build tools used by real staff processing hundreds of thousands of library items. If you want to do meaningful work at the frontier of AI and library systems, this is the role.
Work Schedule: As arranged with supervisor, 20 hours per week, between hours of 7am-6pm Monday-Friday.
Duties:
AI Pipeline Development and Maintenance 50%
- Design, build, and maintain Python automation scripts and API integrations for the AIM cataloging pipeline
- Scan books, CDs, LPs, and other information materials using high resolution and custom-built scanners
- Support physical processing tasks (handling, labeling, barcoding, call number application) as part of automated workflows
- Extend pipeline capabilities, add new media formats, improve confidence scoring models, reduce per-record costs
- Write and maintain unit tests, documentation, and deployment scripts using GitHub
- Monitor production batches, investigate failures, and implement fixes
Custom Solutions and Tool Building 25%
- Build custom automation tools for Content Management workflows using Python, JavaScript, and cloud APIs
- Develop AI-assisted solutions using OpenAI, Anthropic, or open-source LLMs depending on use case
- Automate acquisitions workflows including journal and e-book processing, license tracking, and vendor order management.
- Build automation tools for Electronic Theses and Dissertations (ETD) processing - ingest, metadata generation, repository deposit, and discovery.
- Build staff-facing interfaces that require zero technical knowledge to operate
Cataloging and Metadata 10%
- Assist with quality review of AI-generated MARC records for sound recordings and other material types
- Perform original and copy cataloging using Record Manager as needed
- Validate and clean metadata across Alma ILS, OCLC WorldCat, and digital repository systems
Training 15%
- Assist in supervising Student Technicians on scanning and physical processing workflows
- Train student workers on the Book Scanner app and web UI pipeline tools
- Document workflows, write user guides, and maintain technical knowledge base
- Research & Conference presentations
- Other related functions as assigned.
Required Qualifications:
- Current UT Austin graduate student in good academic standing enrolled for at least nine [9] semester hours during the fall and spring semester and three [3] semester hours during the summer session in Information Science/Studies, Computer Science, Data Science, Library Science, or a related field
- Proficiency in one programming language, Python, JavaScript and others - able to read, write, and debug production-level code independently
- Familiarity with GitHub - branching, committing, pull requests, and collaborative workflows
- Strong analytical and problem-solving skills with attention to detail
- Ability to work independently, manage multiple priorities, and meet deadlines
- Excellent written and verbal communication skills
Preferred Qualifications:
- Experience with REST APIs, JSON/XML data formats, or library systems (Alma, OCLC)
- Familiarity with MARC21, metadata schemas, or cataloging workflows
- Experience with AI tools, LLM APIs (OpenAI, Anthropic), or machine learning pipelines
- Knowledge of cloud platforms (AWS, Azure, GCP) or Infrastructure as Code (Terraform, CloudFormation)
- Experience with web development (FastAPI, Flask, React, or similar)
- Prior research experience, conference presentations, or academic publications
- Interest in robotics, computer vision, or physical automation systems
- Strong information security mindset
We want to emphasize that although experience in certain areas is desirable, candidates who meet the required qualifications and demonstrate excellent promise are encouraged to apply and will be given serious consideration.
Working Conditions: Regular indoor working conditions.
Rate of Pay: $1,733 per month. Exemption from non-resident tuition. Benefits eligible. TRB not available for long semesters.
Applicant Instructions: Applicants should apply with a letter of interest, resume, contact information for three references, links to your GitHub profile and at least one portfolio project demonstrating relevant technical work to:
Kay Ishola
Automation and Integration Librarian
kayode.ishola@austin.utexas.edu
A criminal history background check will be required for finalist(s) under consideration for this position.
Equal Opportunity Employer: The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.