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Information Systems Specialist (AI Literacy and Training Lead

Job in Southwestern Ontario, London, Ontario, Canada
Listing for: Waterloo International
Full Time, Apprenticeship/Internship position
Listed on 2026-09-12
Job specializations:
  • IT/Tech
    AI Business & Operations, Information & Knowledge Management, IT Business Analyst, Technical Writer
Salary/Wage Range or Industry Benchmark: 80248 - 100310 CAD Yearly CAD 80248.00 100310.00 YEAR
Job Description & How to Apply Below

At the University of Waterloo, we create and promote a culture where everyone can reach their full potential. As an employee, you get support & opportunities that empower you to advance your career. Explore how we can bring big ideas to life, together. The University is a welcoming workplace for those of all abilities, interests, and expertise. As part of our workforce, you can do what you do best, every day.

Learn more about our recruitment process.

Department:
Information Systems and Technology - Articifical Intelligence Innovation and Systems Development

Hiring Range: $80,248.28 - $

Time Type:
Full time

Employment Type:

Definite Term

Secondment or contract opportunity. Term: 2 years.

Job Description

Reporting to the Director, AI Innovation and Systems Development, the AI Literacy and Training Lead is an Information Systems Specialist role focused on the adoption, enablement, and responsible use of AI-enabled information systems and services at the University of Waterloo.

The incumbent supports the AI Discovery Lab, the campus-facing front door for AI questions, ideas, training needs, and responsible adoption support.

This role develops and delivers practical AI training, workshops, office hours, documentation, guidance, and reusable learning materials that help staff, teams, and leaders understand how to use AI tools appropriately and effectively in University contexts.

The role works with technical teams, campus partners, service owners, and governance partners to translate emerging AI capabilities, institutional guidance, pilot learnings, and recurring user needs into accessible training and adoption supports.

Key Accountabilities
  • AI Literacy, Training, and Enablement

    Develop and deliver practical AI literacy programming for University audiences, including workshops, office hours, demonstrations, awareness sessions, and team-specific training.

    Design learning supports for users with different levels of AI readiness, from those who are new to AI to early adopters seeking practical guidance.

    Explain AI capabilities, limitations, risks, and responsible-use expectations in clear, audience-appropriate language.

  • Guidance, Documentation, and Learning Materials

    Create and maintain reusable AI guidance, quick-start guides, FAQs, checklists, examples, presentation materials, and other user-facing support resources.

    Convert recurring questions, pilot learnings, and responsible-use expectations into reusable learning assets.

    Contribute to AI Discovery Lab web, knowledge base, or service catalogue content as required.

  • Adoption Support for AI Tools and Pilots

    Support onboarding, training, and adoption activities for approved, pilot, or emerging AI-enabled tools and services.

    Develop user guidance for AI tool pilots, including coding assistants, enterprise AI assistants, productivity tools, or AI-enabled workflow solutions.

    Gather user feedback to identify barriers, learning needs, support gaps, and opportunities to improve adoption.

  • Responsible AI Enablement

    Help users understand privacy, security, data sensitivity, copyright, accessibility, bias, accuracy, and human oversight considerations related to AI use.

    Work with privacy, information security, data governance, procurement, legal, accessibility, records management, and other partners as needed to align training and guidance materials.

    Help users understand when an AI use case may require additional review, escalation, or support.

  • Campus Engagement and Continuous Improvement

    Support AI Discovery Lab events, demonstrations, engagement activities, and communities of practice.

    Track training activity, participation, feedback, recurring questions, and adoption themes.

    Use feedback and service data to improve training materials, workshops, office hours, and guidance.

    Cont…

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