Artificial Intelligence Systems Team Lead, Enterprise Architecture Data Management

About this Role

Summary

The artificial intelligence (AI) systems team lead is responsible for leading the design, build, and deployment of institutional AI services that move from proof of concept into production within defined funding timelines. This role guides a technical team while shaping an AI systems roadmap that supports administrative automation, digital assistant capabilities, teaching and learning initiatives, and research computing. The team lead provides hands‑on technical guidance while coordinating vendors, platforms, and institutional stakeholders to deliver operational AI services. The work focuses on producing measurable outcomes, including adoption, efficiency gains, and visible value from AI investment.

Responsibilities

• Lead AI initiatives from concept to production, delivering measurable value through documented adoption and efficiency gains

• Deliver and maintain an institutional AI services roadmap with defined milestones, adoption targets, and success criteria aligned to funding timelines

• Provide overall technical architecture guidance for AI solutions, including integration patterns, security models, data flows, and platform selection

• Oversee the development and maintenance of AI infrastructure, including model orchestration layers, governance workflows, API integrations, and protected computing environments

• Establish and operate secure AI environments (e.g., sandbox, pilot, and production) to support research, teaching, and administrative use cases

• Lead vendor and tool evaluation, selection, and relationship management for AI platforms and services

• Contribute technical perspective to institutional AI governance processes, risk assessments, and compliance reviews

• Coordinate with internal teams and the broader unit to align AI initiatives with enterprise architecture, identity infrastructure, and integration standards

• Engage with faculty, researchers, and administrative units to identify high‑value AI opportunities and manage expectations

• Report on AI initiative outcomes, including adoption rates, integration health, user feedback, cost avoidance, and risk posture to senior leadership

• Maintain the reliability, performance, and security of AI tools and digital assistant services through established engineering practices

• Adopt and promote responsible AI practices aligned with university policy, unit standards, and applicable regulatory requirements

• Provide technical guidance, mentorship, and workflow planning for team members, and contribute to performance feedback processes as appropriate

• Remain current with AI industry trends, emerging platforms, and leading practices, recommending enhancements aligned with institutional priorities

• Communicate and act in a respectful and professional manner, collaborate effectively, abide by policy, and contribute to a positive and productive work and learning environment

• Engage in continuous learning by participating in activities, training, and events related to Indigenous engagement, reconciliation, equity, diversity, and inclusion

• Demonstrate respect and dignity for all members of the community, actively contribute to an environment of acceptance and inclusion of others, and respond to different perspectives from a place of curiosity, respect, and non‑judgement

• Undertake related duties as assigned, consistent with the nature of the position

Qualifications

• A bachelor's degree in computer science, data science, engineering, or related field

• Minimum of five years of experience in enterprise application development, platform engineering, or systems integration, including experience with secure data pipelines, privacy‑sensitive workloads, or research computing environments, as well as AI governance, model evaluation, risk assessment, and responsible AI practices

• Experience providing leadership and mentorship to a team

• Experience with AI and Machine Learning (ML) systems, cloud‑based AI services, automation platforms, or intelligent workflow systems

• Demonstrated experience delivering AI or automation solutions from proof of concept through production deployment

• Ability to work effectively both independently and collaboratively in a team

• Strong communication skills

• Ability to translate institutional priorities into achievable AI‑enabled solutions

• Strong development skills in Python or Java with solid software engineering fundamentals is preferred

• Proficiency with multi‑agent or generative AI frameworks, AI vendor management, or higher education IT environments is an asset

Equal Employment Opportunity Statement

The University of Saskatchewan aspires to be what the world needs and embraces equity, diversity and inclusion as foundational to excellence and innovation. We actively seek to create a welcoming environment where all individuals feel empowered to thrive, contribute, and grow. Applications from equity‑deserving groups are encouraged as part of our ongoing efforts to reflect the diversity of the communities we serve. We continue to grow our partnerships with Indigenous communities across the province, nationally, and internationally and value the unique perspective that Indigenous employees provide to strengthen these relationships. Verification of Indigenous membership/citizenship at the University of Saskatchewan is led and determined by the DEYBWEWIN taapwaywin tapwewin: Indigenous Truth policy and the Standing Committee in accordance with the processes developed to enact the policy. Successful candidates that assert Indigenous membership/citizenship will be asked to complete the verification process of Indigenous membership/citizenship with documentation. The University of Saskatchewan provides an accessible and inclusive workplace. Should you require support through any stage of the recruitment process, contact us for assistance.

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