Artificial Intelligence Systems Team Lead,Enterprise Architecture Data Management Job Saskatoon area,Saskatchewan Canada,IT/Tech

Artificial Intelligence Systems Team Lead, Enterprise Architecture Data Management

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.

Duties and Responsibilities:

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

Delivers and maintains an institutional AI services roadmap with defined milestones, adoption targets, and success criteria aligned to funding timelines

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

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

Establishes and operates secure AI environments (, sandbox, pilot, and production) to support research, teaching, and administrative use cases

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

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

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

Engages with faculty, researchers, and administrative units to identify high-value AI opportunities and manage expectations

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

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

Adopts and promotes responsible AI practices aligned with university policy, unit standards, and applicable regulatory requirements

Provides technical guidance, mentorship, and workflow planning for team members, and contributes to performance feedback processes as appropriate

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

Communicates and acts in a respectful and professional manner, collaborates effectively, abides by policy, and contributes to a positive and productive work and learning environment

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

Demonstrates respect and dignity for all members of the community, actively contributes to an environment of acceptance and inclusion of others, and responds to different perspectives from a place of curiosity, respect, and non-judgement

Undertakes related duties as assigned, consistent with the nature of the position

Qualifications:

A bachelor’s degree in computer science, data science, engineering, or a 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 form proof of concept through production…