Principal, AI Enablement, Tools and Accelerators

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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.

Responsibilities:

Key Responsibilities

AI Enablement Strategy & Enterprise Adoption

• 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.

AI Tools, Accelerators & Reuse

• 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.

Agentic AI Readiness

• 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.

Cross Platform & Cross Function Coordination

• 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.

Central to Execution Operating Model

• 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.

Future Facing Capability Development

• 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.

Leadership & Operating Style

• Enterprise minded systems thinker who sees connections across platforms, teams, and domains.
• Comfortable operating in ambiguity and shaping new capability areas.
• Collaborative leader who enables others rather than centralizing execution.
• Pragmatic, outcome oriented, and focused on scale, reuse, and adoption.

Qualifications

Required

• 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.

Preferred

• 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.

Conditions of Employment:

Candidates must be eligible to work in the country of interest at the time any offer of employment is made and are responsible for obtaining any required work permits, visas, or other authorizations necessary for employment. Prior to their start date, candidates will also need to provide proof of their eligibility to work in the country of interest.

Linguistic Requirements

Based on equal qualifications, preference will be given to bilingual candidates.

Diversity and Inclusion

Air Canada is strongly committed to Diversity and Inclusion and aims to create a healthy, accessible and rewarding work environment which highlights employees’ unique contributions to our company’s success.

As an equal opportunity employer, we welcome applications from all to help us build a diverse workforce which reflects the diversity of our customers, and communities, in which we live and serve.

Air Canada thanks all candidates for their interest; however only those selected to continue in the process will be contacted.