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The Manager, Data & AI leads the technical integration, deployment and production-readiness capabilities required to operationalize AI products, models, agents and supporting data pipelines across Air Canada’s enterprise environments. The role ensures that AI solutions move from approved architecture and engineering designs into development, test and production in a secure, controlled, repeatable and increasingly automated manner. The Manager leads AI Systems Integrators and Deployment Specialists, establishes reusable integration and deployment patterns, and works across AI Engineering, Data Engineering, Platform Engineering, Architecture, Cybersecurity, Cloud Operations and DataOps to deliver supportable production outcomes. The role balances engineering velocity with enterprise governance, operational stability, traceability and risk-based controls.

This position may be located in Montreal or Toronto.

Responsibilities

- Lead the AI Systems Integration capability and manage the specialists responsible for moving AI solutions from approved designs into enterprise environments.
- Ensure AI products, models, agents, APIs and supporting data pipelines are properly integrated with enterprise platforms and upstream and downstream systems.
- Oversee deployment and configuration of AI workloads across development, test and production environments.
- Drive approved infrastructure-as-code, CI/CD, MLOps and LLMOps patterns, including application and model promotion, versioning, rollback and environment management.




- Establish reusable integration patterns, deployment components, templates and automation to reduce solution-specific engineering effort and accelerate adoption.
- Partner with AI Product Managers, Data Scientists, AI Engineers, Solution and Enterprise Architects, Cybersecurity, Cloud Operations, Platform Engineering and DataOps to translate designs into production-ready implementations.
- Establish and enforce production-readiness criteria, including monitoring, logging, alerting, runbooks, support documentation, operational ownership and recovery procedures.
- Ensure integrations and deployments satisfy Architecture, Cybersecurity, Infrastructure, Data Governance, Privacy and operational requirements.
- Implement risk-based controls for solutions involving sensitive data, AI models, autonomous agents or material business decisions, including appropriate human approval points.
- Lead technical validation, go-live readiness, post-deployment verification and orderly transition to steady-state operational support.
- Define and track measures for deployment success, integration quality, automation, reliability, rework and operational readiness.
- Identify recurring integration and deployment issues and improve engineering practices, standards and reusable tooling upstream.
- Manage demand, priorities, capacity,



dependencies and delivery commitments for the AI Systems Integration function.
- Lead, coach and develop a high-performing technical team, establish clear accountabilities and support career growth.
- Provide leadership during complex or high-risk implementations and act as an escalation point for integration and deployment issues.
- Manage relationships with external technology partners and vendors that complement internal delivery capabilities.
- Maintain current knowledge of AI, cloud, integration, deployment and production-engineering practices and assess their applicability to Air Canada.

Qualifications

- University degree in Computer Science, Engineering, Information Technology or a related discipline, and/or equivalent relevant professional experience.
- 7+ years of progressive technology experience, including 3+ years leading technical teams in a large, complex enterprise.
- Demonstrated experience in systems integration, cloud engineering, platform engineering, DevOps, software delivery or production operations.
- Robust understanding of CI/CD, Git-based source control, branching strategies, automated testing, infrastructure as code, deployment pipelines and environment promotion.
- Working knowledge of modern Data and AI ecosystems, ideally including Azure, Snowflake, Databricks, Azure DevOps or GitHub, orchestration platforms and AI/ML deployment tooling.
- Understanding of MLOps and LLMOps concepts, model and application deployment, versioning, observability and production lifecycle management.
- Experience integrating APIs, data pipelines, cloud services, identity and access controls, enterprise applications and event-driven compo

📌 Manager, Data and AI (Toronto)
🏢 Air Canada
📍 Toronto