AI Engineer

Details

Open Date 05/19/2026

Requisition Number PRN45104B

Job Title Artificial Intelligence (AI) / Machine Learning (ML) Engineers

Working Title AI Engineer

Career Progression Track P00

Track Level P4 - Advanced, P3 - Career

FLSA Code Computer Employee

Patient Sensitive Job Code? No

Standard Hours per Week 40

Full Time or Part Time? Full Time

Shift Day

Work Schedule Summary

Monday – Friday 8am-5pm.

VP Area Academic Affairs

Department 00810 - Scient Comp & Imag Instit-Oper

Location Campus

City Salt Lake City, UT

Type of Recruitment External Posting

Pay Rate Range 100,000-135,000

Close Date 08/19/2026

Priority Review Date (Note - Posting may close at any time)

Job Summary

The AI Engineers Program is a core component of Utah RAISE (Research & AI Infrastructure for a Statewide Ecosystem) and the broader University of Utah AI ecosystem. The program provides applied AI engineering expertise to complement the shared computing infrastructure to enable researchers, educators, and administrators at the U to adopt responsible and scalable AI adoption.

We are hiring a cohort of AI Engineers who can support design, development, and deployment of prototype to production-grade AI solutions for well-scoped and high-impact use cases. This cohort will focus on application-level work: model fine-tuning and adaptation, retrieval-augmented generation pipelines, agentic systems, and production-oriented ML engineering, and will help build durable, in‑house capacity to support teaching, research, and innovation across the university.

The AI Engineers Program will be administered by the SCI Institute in coordination with the Office of Artificial Intelligence and the One-U Responsible AI Initiative to serve the broader University of Utah community and beyond.

Responsibilities

• Accelerate responsible AI integration across teaching and research, helping faculty and students move from ideas to production ready tools and prototypes.

• Support rapid experimentation, prototyping, and implementation, which is increasingly critical given how quickly AI technologies are evolving.

• Build and maintain shared tools, frameworks, and pipelines that can be reused across colleges and initiatives, reducing duplication and dependence on external vendors.

• Help operationalize governance, privacy, and security expectations by embedding them directly into AI solutions.

• Act as force multipliers, upskilling internal teams and supporting interdisciplinary collaboration.

• Collaborate with faculty, researchers, and other institutional partners to scope projects and define technical approaches.

• Provide mentorship and technical guidance to senior undergraduate and MS students in AI technologies and application development.

• Contribute to open-source software and promote reproducible research practices, helping to foster a culture of transparency and reuse across campus.

• Design and deliver workshops, training sessions, and educational materials on AI tools and methods.

Provide technical consulting to the campus community through structured office hours and project-based engagements.

Minimum Qualifications

• Requires a bachelor’s (or equivalency) + 6 years or a master’s (or equivalency) + 4 years of directly related work experience. Assumes work equivalency (1 year of higher education can be substituted for 1 year of directly related work experience).

• Professional experience working in technical roles involving complex software‑based systems, research computing environments, or data‑driven applications, with responsibilities beyond routine execution.

• Evidence of applying advanced technical concepts independently, including systems design, problem decomposition, and implementation choices, in environments with incomplete or evolving requirements.

• Demonstrated experience collaborating with non‑peer stakeholders (e.g., researchers, faculty, clients, domain experts, or organizational partners) to translate needs or ideas into technical work.

• Professional experience operating in environments requiring judgment, discretion, and ethical or policy awareness, such as academic, research, healthcare, government, regulated industry, or similarly constrained settings.

• Prior experience guiding or supporting others’ technical work, such as mentoring, advising, leading technical components of projects, or providing consultative support.

Demonstrated ability to communicate technical work clearly in written and verbal form to audiences with varying levels of technical expertise.

Preferences

• Demonstrated ability to effectively collaborate with researchers and stakeholders across disciplines and levels of technical expertise.

• Experience in one or more relevant technical domains supporting applied AI development, such as machine learning systems engineering, LLM /GenAI application development, software engineering (e.g., Python, C++, JavaScript), cloud computing, distributed systems, or full-stack development

• Broad familiarity with AI and research computing and data practices, with the ability to apply sound technical judgment to design, build, and deploy projects with a high degree of independence and creativity.

• Ability to identify collaboration opportunities and initiatives that would benefit from applied AI integration and partnership with SCI and related programs.

• Demonstrated experience developing and applying AI/ML techniques (e.g., model training and fine-tuning, large language models, retrieval-augmented generation, or scalable ML systems) in research, scientific, or production-oriented contexts.

Type Benefited Staff

Special Instructions Summary

Additional Information

The University is a participating employer with Utah Retirement Systems (“URS”). Eligible new hires with prior URS service, may elect to enroll in URS if they make the election before they become eligible for retirement (usually the first day of work). Contact Human Resources at View phone number on click.appcast.io for information. Individuals who previously retired and are receiving monthly retirement benefits from URS are subject to URS’ post-retirement rules and restrictions. Please contact Utah Retirement Systems at View phone number on click.appcast.io or View phone number on click.appcast.io or University Human Resource Management at View phone number on click.appcast.io if you have questions regarding the post-retirement rules.

This position may require the successful completion of a criminal background check and/or drug screen.

The University of Utah values candidates who have experience working in settings with students and possess a strong commitment to improving access to higher education.

Veterans’ preference is extended to qualified applicants, upon request and consistent with University policy and Utah state law. Upon request, reasonable accommodations in the application process will be provided to individuals with disabilities.

Consistent with state and federal law, the University of Utah does not discriminate based upon race, ethnicity, color, religion, national origin, age, disability, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, pregnancy-related conditions, genetic information, or protected veteran’s status. The University does not discriminate on the basis of sex in the education program or activity that it operates, as required by Title IX and 34 CFR part 106. The requirement not to discriminate in education programs or activities extends to admission and employment. Inquiries about the application of Title IX and its regulations may be referred to the Title IX Coordinator, to the Department of Education, Office for Civil Rights, or both.

To request a reasonable accommodation for a disability or if you or someone you know has experienced discrimination or sexual misconduct including sexual harassment, you may contact the Director/Title IX Coordinator in the Office of Equal Opportunity and Title IX ( OEO ). More information, including the Director/Title IX Coordinator’s office address, electronic mail address, and telephone number can be located at the: University of Utah Non‑Discrimination page .

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As per University of Utah policy 5-108: Transfer of Benefits Eligible Staff Members , a new hire to the University of Utah who is still serving a 12 month probationary period will not be hired into another University of Utah job (a transfer) until the successful completion of the probationary period.