Principal, AI Enablement, Tools and Accelerators

Air Canada•Toronto, ON

11d

About The Position

Being part of Air Canada is to become part of an iconic Canadian symbol, recently ranked the best Airline in North America. Let your career take flight by joining our diverse and vibrant team at the leading edge of passenger aviation. Air Canada is accelerating the adoption of AI across the enterprise to drive measurable business impact, scale intelligent automation, and embed AI into day to day execution. A critical success factor is the ability to enable teams consistently, reuse what works, and translate central AI capabilities into scalable, front line execution across business domains. The Principal, AI Enablement, Tools & Accelerators is accountable for shaping and guiding the enterprise AI enablement, tools, and accelerators strategy. This role shapes how AI capabilities—including reusable accelerators and agentic AI patterns—are introduced, governed, and scaled across the organization. The focus is on enablement, reuse, and adoption at scale, rather than bespoke delivery. Operating at the intersection of AI strategy, platforms, data science, delivery, and governance, this role connects central AI capabilities with forward deployed execution models across the enterprise. The Senior Manager ensures that AI investments translate into consistent execution, faster time to value, and sustainable scale, while enabling domain specific innovation.

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
5+ years of experience across data, AI, software engineering, digital platforms, or technology delivery environments.
Proven experience defining or leading enablement, platform adoption, or reusable capability strategies at enterprise scale.
Strong understanding of modern AI/ML and GenAI concepts, including tooling, lifecycle management, and operationalization.
Demonstrated ability to operate across strategy and execution—translating vision into scalable, practical outcomes.
Proven ability to influence and align senior technical and business stakeholders.
Demonstrate punctuality and dependability to support overall team success in a fast-paced environment.
Strong communication skills, with the ability to clearly articulate complex concepts to diverse audiences.

Nice To Haves

Experience with agentic AI concepts, orchestration frameworks, or AI driven workflow automation.
Exposure to multi cloud or hybrid enterprise environments (e.g., AWS and Azure).
Familiarity with Responsible AI, governance, privacy, and risk management practices.
Experience working in large, regulated, or operationally complex environments.
Background in building internal platforms, accelerators, or communities of practice.

Responsibilities

Shape and guide the enterprise AI enablement strategy, aligned to the broader Data & AI mandate and operating model.
Establish a clear roadmap for how AI tools, accelerators, and execution patterns are adopted across the enterprise.
Ensure AI enablement balances central consistency with flexibility for business and domain specific needs.
Partner with business, digital, and technology leaders to assess AI readiness and support adoption at scale.
Define the enterprise strategy for reusable AI accelerators, including identification, prioritization, lifecycle management, and adoption.
Establish mechanisms to catalogue, govern, and promote reuse of AI assets across platforms and delivery teams.
Partner with platform, engineering, and data science teams to ensure accelerators are production ready, secure, and scalable.
Enable a “build once, scale many” approach to AI capabilities across the organization.
Own the agentic AI readiness strategy, including enterprise patterns, guardrails, and adoption pathways.
Partner with Architecture, Security, Privacy, and Responsible AI teams to ensure agentic approaches align with enterprise standards and risk posture.
Translate emerging agentic AI trends into pragmatic, enterprise appropriate guidance for teams.
Support the responsible introduction of agentic workflows, including human in the loop and operational control models.
Act as a connective layer across AI platforms (e.g., data platforms, ML platforms, GenAI platforms), data science teams, delivery organizations, governance bodies, and strategy functions.
Coordinate enablement efforts across AWS, Azure, and other enterprise platforms, ensuring alignment while respecting platform specific strengths.
Reduce fragmentation by aligning enablement, tooling, and accelerator efforts across the enterprise.
Define and operationalize how central AI capabilities connect to forward deployed execution models embedded within business and delivery teams.
Enable consistent execution patterns without centralizing delivery ownership.
Support scalable operating models that accelerate adoption while maintaining quality, security, and governance.
Monitor industry trends in AI enablement, agentic systems, developer and data scientist productivity, and intelligent execution models.
Continuously evolve AI enablement strategies as technologies, platforms, and operating models mature.
Serve as a thought partner to senior leadership on how AI enablement must evolve to support long term enterprise goals.