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Sr. Manager IT Operations - Network Operations, Performance & Capacity, and Automation
TD
Mississauga, ON
- Full-time
The Senior Manager leads a complex, geographically distributed operational organization and sets direction across multiple disciplines. The incumbent is accountable for translating…
Added 2 mins ago
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Manager, Business Systems Analysis, TD Securities
TD
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- Full-time
…scalable, and resilient solutions that support business growth, operational excellence, and risk…
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Added 32 mins ago
AC
Manager, Data and AI - AI Systems Integrations and Agentic technical owner
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Toronto, ON · Dorval, QC
- Full-time
The Manager, Data & AI leads the technical integration, deployment and production-readiness capabilities required to operationalize AI products, models, agents and supporting data pipelines…
Added 47 mins ago
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Added 47 mins ago
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Investigations Manager, Canada East
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Added 48 mins ago
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Sr. Business Systems Analyst, TD Securities
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…scalable, and resilient solutions that support business growth, operational excellence, and risk…
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Sr. Business Systems Analyst, TD Securities
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Own operational and process-related analysis and delivery

Air Canada

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

Toronto, ON, Canada
Dorval, QC, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Nov 19, 2026
Experience: 7+ years of progressive technology experience, including 3+ years leading technical teams in a large, complex enterprise.
Posting language: English
Posted: Nov 5, 2026

Original 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.

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.

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More about this job

Responsibilities

The Manager leads the technical integration, deployment, and production-readiness of AI products, models, and agents across enterprise environments. They oversee a team of specialists to ensure AI solutions are securely and reliably integrated into production while balancing engineering velocity with governance.

Requirements

Candidates must have a university degree in a relevant technical discipline and at least 7 years of progressive technology experience. Proven expertise in systems integration, cloud engineering, and leading technical teams within a large, complex enterprise is required.

Skills

AI Systems Integration
MLOps
LLMOps
Cloud Engineering
Platform Engineering
CI/CD
Infrastructure as Code
Data Engineering
API Integration
Enterprise Architecture
Cybersecurity
Data Governance
Team Leadership
Stakeholder Management
Production Operations
Software Delivery

Visa sponsorship

Not detected in the job text

Keywords

AI
Data
Systems Integration
MLOps
LLMOps
Azure
Snowflake
Databricks
Azure DevOps
GitHub
CI/CD
Infrastructure as Code
API
DataOps
Cloud Operations
Enterprise Architecture
Cybersecurity
Production Readiness
Automation
Version Control
Observability
Identity and Access Management
IT Service Management
Aviation
Software Delivery
Platform Engineering
Deployment Pipelines
Risk Management
Technical Leadership
Data Governance

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