Job Description

Responsibilities


Partner closely with academic and administrative departments to understand their goals, challenges, and concerns, and to identify where AI can thoughtfully add value—with an emphasis on improving efficiency, decision‑making, and student success.
Identify, assess, and help prioritize AI use cases that balance innovation with institutional risk, ensuring solutions are appropriate, feasible, and aligned with university needs.
Collaborate with IT colleagues to design, pilot, and evaluate AI-enabled solutions, including configuration and integrations with existing systems and platforms, while ensuring data quality, security, and reliability.
Serve as a trusted advisor on AI best practices, helping campus partners understand what is possible, what is appropriate, and what requires caution, especially when working with sensitive or regulated data.
Work closely with legal, compliance, and data governance partners to assess risks, protect institutional and student data, and ensure AI solutions meet privacy, security, and regulatory requirements.
Lead or support the full lifecycle of AI initiatives—from exploration and proof-of-concept through implementation, change management, and adoption—providing hands-on assistance with setup, testing, troubleshooting, documentation, and operational handoff.
Conduct feasibility assessments and post-implementation reviews to evaluate outcomes against defined metrics, gather feedback, and inform continuous improvement.
Define success metrics and baselines for AI initiatives (e.g., cycle time, workload reduction, cost avoidance, service levels, satisfaction, adoption/usage, and compliance/risk indicators) and measure ROI through post-implementation reporting and continuous optimization.
Provide direct, hands-on support to campus partners during and after deployments (e.g., guided onboarding, testing, issue triage, and coordination with vendors and internal support teams) to ensure solutions are adopted and sustained.
Help build campus understanding and confidence around AI by developing and delivering training sessions, workshops, and documentation that promote responsible use, adherence to data governance requirements, privacy awareness, and ethical considerations.
Translate complex AI concepts into clear, accessible language for audiences with varying levels of technical expertise.
Stay informed about emerging AI trends and tools, bringing forward ideas that are forward‑looking yet practical.
Contribute to the development of a measured, strategic roadmap for integrating AI into university systems and processes, prioritizing initiatives that deliver clear value while protecting data and minimizing risk.
Qualifications
Bachelor's degree in computer science, information technology, artificial intelligence, data science or related field. Master's degree preferred.
At least 1- 2 years of experience designing and implementing AI and/or data solutions, preferably in a higher education; preference will be given to candidates with AI project support experience or other technical consulting roles of similar scope and impact.
Strong knowledge of applied AI/ML, including natural language processing and common higher education use cases.
Experience assessing stakeholder needs, defining scopes, and delivering AI initiatives; understanding of IT infrastructure and data governance.
Experience driving enablement and adoption for new tools (communications, training, and change management).
Hands-on experience supporting AI solutions from implementation through steady state (configuration/testing, troubleshooting, onboarding/documentation), coordinating with vendors and internal teams as needed.
Project management skills to manage competing priorities, meet deadlines, and drive change through to completion.
Strong analytical and problem solving skills, with sound judgment and a practical approach to solution design.
Knowledge of AI ethics, privacy (e.g., FERPA and applicable state regulations), and information security best practices.
Collaborative, customer oriented approach; able to learn new tools quickly and work effectively with cross functional partners.
Strong written and verbal communication skills; able to translate technical concepts for non-technical audiences.