Manager, Data and AI - AI Systems Integrations and Agentic technical owner

Air Canada; Toronto; On-site; CAD 120,000 - 180,000; Full time

Job summary

Air Canada seeks a Manager, Data & AI to lead the integration, deployment and production-readiness of AI products, models and data pipelines across Air Canada’s enterprise environments.

You will supervise AI Systems Integrators and Deployment Specialists, establish reusable patterns, and work with Architecture, Cybersecurity, Cloud Operations and DataOps to deliver scalable, secure AI solutions.

Qualifications

• University degree in Computer Science, Engineering, Information Technology or related discipline.
• 7+ years of progressive technology experience with 3+ years leading technical teams.
• Demonstrated experience in systems integration, cloud engineering, platform engineering, DevOps, software delivery or production operations.
• Strong understanding of CI/CD, Git-based source control, automated testing, infrastructure as code, deployment pipelines and environment promotion.
• Working knowledge of data and AI ecosystems (Azure, Snowflake, Databricks, Azure DevOps or GitHub).
• Understanding of MLOps and LLMOps concepts, model and deployment lifecycle management.
• Experience integrating APIs, data pipelines, cloud services, and enterprise apps.
• Strong knowledge of enterprise Architecture, Cybersecurity, Change and IT Service Management practices.
• Proven ability to balance governance with delivery velocity and automation.
• Demonstrated leadership, stakeholder management and communication skills.

Responsibilities

• Lead the AI Systems Integration capability and manage specialists moving AI solutions into enterprise environments.
• Ensure AI products and data pipelines integrate with enterprise platforms and systems.
• Oversee deployment across development, test and production environments.
• Drive infrastructure-as-code, CI/CD, MLOps and LLMOps patterns with proper versioning and rollback.
• Establish reusable deployment patterns and automation to accelerate adoption.
• Collaborate with product managers, data scientists, engineers, architects and cybersecurity teams to productionize designs.
• Define production-readiness criteria including monitoring, logging and runbooks.

Skills

Technical leadership

Systems integration

Cloud engineering

DevOps / CI/CD

AI/ML deployment

Data ecosystems

Architecture governance

Security & compliance

Stakeholder management

Communication

Education

Bachelor's degree in CS/Engineering

Tools

Azure

Snowflake

Databricks

Azure DevOps

GitHub

Orchestration platforms

AI/ML deployment tools

Job description

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.

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.
• 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.

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.