Job Description

Position Summary
Under the supervision of the Director of Administrative Systems, leads SUU’s AI engineering practice and serves as the University’s subject-matter expert on artificial intelligence. Directs the architecture, development, validation, and deployment of AI-powered applications supporting the University’s administrative systems and AI initiatives. Defines the team’s roadmap and priorities, oversees the integration of AI solutions into existing systems and workflows, and ensures scalability, security, reliability, and compliance with data privacy regulations and ethical standards. Contributes directly to codebases as a functional software engineer.Supervises and mentors the student programmer squad (approximately 10 students) and serves as the technical escalation point when student programmers assist campus departments on AI tasks. Acts as SUU’s campus-facing AI expert and evangelist — partnering with the Center for Teaching Innovation (CTI) and other campus units on AI training direction, serving as a technical escalation resource for emerging campus AI support efforts and peer-champion programs, contributing to institutional AI policy, helping dispel faculty and staff apprehension while championing practical and responsible use, and representing SUU on system-wide AI initiatives

Essential Functions
AI engineering and software development. Direct the architecture, coding, development, validation, and deployment of AI-powered applications supporting University administrative systems and AI initiatives. Build and integrate AI/ML solutions (e.g., agentic systems, LLM integration, retrieval, automation) into existing workflows using the department’s modern stack (Python, FastAPI, React, PostgreSQL). Ensure scalability, security, and reliability of AI systems; implement best practices for AI model selection, deployment, monitoring, and maintenance; ensure compliance with data privacy regulations (including FERPA) and emerging institutional AI ethics standards. Contribute directly to codebases as a hands-on engineer, including architectural decisions, code reviews, technical standards, automated tests, documentation, and deployment processes.
Team leadership and mentorship of student programmers. Define the team’s roadmap, success metrics, and priorities in collaboration with the Director and Assistant Director. Onboard new student programmers; assign and prioritize work; conduct code reviews; run standups and sprint demos; mentor students and identify and develop squad leads. Ensure student produced code meets departmental quality and security standards before merging. Serve as the primary technical point of contact for student programmers on day-to-day work, and as the escalation resource when student programmers assist campus departments on AI tasks.
Campus AI subject-matter expert and evangelist. Serve as SUU’s campus-facing AI resource. Provide technical escalation support for emerging campus AI support efforts and peer champion programs; build trust and partnership with faculty, staff, and administrators; help dispel apprehension around AI while championing practical and responsible use; identify and 20%surface high-leverage AI opportunities across departments. Coach and equip student programmers and other campus AI advocates to extend that reach.
AI strategy, policy, and external representation. Advise CTI and other University units on AI training direction and curriculum needs. Contribute to drafting and maintaining institutional AI policy and responsible-use guidelines. Represent SUU on system-wide and inter-institutional AI initiatives as designated (e.g., the University of Utah AI Supercomputer executive steering committee).
Stakeholder collaboration. Collaborate with system users, campus stakeholders, and department leadership to gather requirements, validate functionality, and troubleshoot software applications. Translate stakeholder needs into well-scoped tickets appropriate for student programmers. Coordinate with the Assistant Director and full-time engineering team on dependencies, integrations, and handoffs.
Administer the student programmer program, including recruitment coordination with campus departments, interviewing candidates, running automated onboarding and offboarding processes, and maintaining program documentation.
Other duties as assigned.


Education & Experience
Minimum Qualifications

Bachelor’s degree in Computer Science or closely related field (e.g., software engineering, computer engineering, information systems, data science).
Demonstrated software development experience using modern web frameworks.
Experience designing, building, or integrating AI agentic systems and LLM-based applications in production (beyond prompt usage).
Hands-on AI programming experience (e.g., agent frameworks, tool use, retrieval-augmented generation, model integration, AI-assisted development workflows).
Experience deploying, monitoring, and maintaining AI/ML solutions integrated with existing systems and workflows.
Experience leading or mentoring student programmers, junior developers, or technical teams.
Strong interpersonal skills and an outgoing communication style; demonstrated ability to build trust and work effectively with nontechnical audiences, including faculty and senior administrators.
Strong written and verbal communication skills, including the ability to explain AI concepts to a general audience and to provide clear technical guidance to junior developers.
Working knowledge of data privacy and ethical considerations in AI projects.
Willingness to maintain current knowledge and adapt as AI tooling evolves rapidly. Ability to relate well with staff, faculty, students, administrators, and other IT staff.
Ability to work quickly and accurately, manage a diverse workload, and complete tasks in a timely manner.
Preferred Qualifications
Professional software engineering experience (industry, research lab, or comparable production-software role) — strongly preferred, particularly for candidates whose degree is in a field other than Computer Science.
Experience presenting, teaching, or training on AI or technical topics to mixed audiences (faculty, staff, students).
Experience contributing to AI policy, governance, or responsible-AI guidelines.
Experience using AI tools in software development (e.g., Claude Code, Copilot, or similar AI-assisted development tools).
Experience with Python, FastAPI, React, and PostgreSQL.
Experience conducting code reviews and establishing development standards.
Knowledge of SQL, PL/SQL, Oracle, macOS, Linux, and Docker. Familiarity with Git-based workflows, CI/CD pipelines, and modern software development practices.
Knowledge of IT security and its application in the higher education environment.
Experience integrating systems via data push/pull processes.
Familiarity with higher education environments and faculty culture.
Professional software engineering experience is strongly preferred in addition to the educational requirement.