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Air Canada's Data Science and Artificial Intelligence team designs the machine learning models, optimization engines, and AI agents that support Customer Service, Operations, Commercial Affairs, and Corporate Services functions. The team is distributed across specialized units aligned with the business, each possessing a product portfolio ranging from the initial idea to production and implementation.

As Principal Manager - Artificial Intelligence, the incumbent will lead a portfolio of AI solutions for one or more business domains, including corporate services (Human Resources, Legal Affairs, Information Technology, and Procurement), as well as a service-wide AI engineering practice domain, such as machine learning and machine learning operations, or the design and evaluation of AI agents. This person will be responsible for the delivery and execution of machine learning and AI agent solutions, and ensuring that each model and agent is of measurable reliability prior to launch and maintenance in production.

The chosen candidate will lead a portfolio of AI implementation and workflow teams, directly and through technical managers, including AI systems developers, data scientists, and machine learning operations specialists, and will work in close collaboration with key assigned stakeholders and IT, Architecture, and Cybersecurity departments.

The successful candidate will report to the Director - Data Science and Artificial Intelligence.

Responsibilities :





- Ensure the execution of the AI portfolio of assigned business domains (e.g., HR, Legal Affairs, IT, and Procurement): transform opportunities prioritized by the AI governance process into functional machine learning and AI agent solutions, with clear value milestones agreed upon with assigned stakeholders.
- Define the AI strategy and roadmap for the assigned portfolio and practice domain, in collaboration with the Director - Data Science and Artificial Intelligence.
- Lead and build a team of technical managers, AI systems developers, data scientists, and machine learning operations specialists, taking notably into account objectives, coaching, performance, and career development.
- Handle recruitment, selection, and onboarding, as well as maintaining a high level of employee engagement within the team.
- Manage and allocate the capacity, budget, and external resources necessary for the implementation of the assigned portfolio and practice domain, balancing competing priorities and providing effort and resource estimates to the governance process when new opportunities are evaluated.
- Ensure that solutions in production are monitored, supported, and continuously improved. Communicate their accuracy, adoption, and value to assigned stakeholders and senior management.
- Act as the subject matter expert resource for the service in their area of expertise (machine learning, machine learning operations, AI agents)



and advise all teams on approach, architecture, and risks.
- Apply and promote an evaluation-driven design approach: success criteria and evaluation methods are agreed upon with business experts before construction begins, and each model and agent must achieve agreed accuracy and safety thresholds before production deployment.
- Contribute to the definition and updating of the service’s standard stack, reusable templates, and machine learning operations practices so that teams move from prototype to production quickly and consistently.
- Ensure that AI solutions are deployed through continuous integration and deployment pipelines with automated testing and evaluation controls.
- Establish standards for code quality, security, monitoring, and production support across the service.
- Act as the primary technical counterpart of the service with IT, Architecture, Cybersecurity, and other implementation teams, influencing cross-functional priorities and decisions and resolving systemic roadblocks related to environments, access, and platforms.
- Ensure that responsible AI, security, and privacy reviews are conducted in collaboration with Cybersecurity, Legal Affairs, and Privacy, as needed.
- Lead the service community of practice in their area of expertise, anticipate future capacity and skills needs, refine team expertise, and keep tools and practices up to date as the field evolves.

Qualifications

- At least eight years of experience in machine learning, AI systems development, data science, or software engineering, including at least five years in personnel management (hiring, performance, development), and experience in leadership thr

📌 Principal Manager (Dorval)
🏢 Air Canada
📍 Dorval