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About the Role

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. This role ensures AI solutions move securely and efficiently from design to production, balancing engineering velocity with enterprise governance and operational stability.

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.

Requirements

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.
Strong 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 components.
Strong knowledge of enterprise Architecture, Cybersecurity, Change, Release, and IT Service Management practices.
Demonstrated ability to balance governance, production risk, and controls with delivery velocity and automation.
Proven people leadership, stakeholder management, communication, decision-making, and problem-solving capabilities.
Demonstrate punctuality and dependability to support overall team success in a fast-paced environment.
Experience in aviation, transportation, or another highly regulated, operationally critical industry is an asset.
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.

Skills

AI
Data Integration
Deployment
Production Readiness
AI Products
AI Models
AI Agents
Data Pipelines
Enterprise Environments
Secure Integration
Controlled Deployment
Repeatable Deployment
Automated Deployment
AI Systems Integration
Deployment Specialists
Reusable Integration Patterns
Deployment Patterns
AI Engineering
Data Engineering
Platform Engineering
Cybersecurity
Cloud Operations
DataOps
Engineering Velocity
Enterprise Governance
Operational Stability
Traceability
Risk-based Controls
APIs
Enterprise Platforms
Upstream Systems
Downstream Systems
AI Workloads
Development Environments
Test Environments
Production Environments
Infrastructure-as-Code
CI/CD
MLOps
LLMOps
Application Promotion
Model Promotion
Versioning
Rollback
Environment Management
Deployment Components
Templates
Automation
Solution Engineering
Adoption Acceleration
AI Product Managers
Data Scientists
Solution Architects
Enterprise Architects
Production-Readiness Criteria
Monitoring
Logging
Alerting
Runbooks
Support Documentation
Operational Ownership
Recovery Procedures
Architecture Requirements
Cybersecurity Requirements
Infrastructure Requirements
Data Governance Requirements
Privacy Requirements
Operational Requirements
Sensitive Data Controls
AI Model Controls
Autonomous Agent Controls
Material Business Decision Controls
Human Approval Points
Technical Validation
Go-Live Readiness
Post-Deployment Verification
Steady-State Operational Support
Deployment Success Metrics
Integration Quality Metrics
Automation Metrics
Reliability Metrics
Rework Metrics
Operational Readiness Metrics
Engineering Practices
Standards
Reusable Tooling
Demand Management
Priority Management
Capacity Management
Dependency Management
Delivery Commitments
Team Leadership
Coaching
Development
Accountability
Career Growth
Complex Implementations
High-Risk Implementations
Escalation Point
External Technology Partners
Vendor Management
Cloud Engineering
Modern Data Ecosystems
Azure
Snowflake
Databricks
Azure DevOps
GitHub
Orchestration Platforms
AI/ML Deployment Tooling
MLOps Concepts
LLMOps Concepts
Model Deployment
Application Deployment
Observability
Production Lifecycle Management
Cloud Services
Identity and Access Controls
Enterprise Applications
Event-Driven Components
Enterprise Architecture
Change Management
Release Management
IT Service Management
Stakeholder Management
Communication
Decision-Making
Problem-Solving
Punctuality
Dependability
Aviation Industry
Transportation Industry
Regulated Industries
Operationally Critical Industries

Location

Montreal
Toronto

Work Type

Full-time

Experience Level

Manager
7+ years of progressive technology experience
3+ years leading technical teams

Education Level

University degree in Computer Science, Engineering, Information Technology or a related discipline
Equivalent relevant professional experience

About the Company

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.

Equal Opportunity

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.