Data and Artificial Intelligence Service Manager - Technical Lead - Systems and Solutions Integration

Being part of Air Canada means being part of a Canadian icon, Air Canada recently voted Best Airline in North America. Take your career to new heights by joining our innovative and diverse team at the forefront of passenger air transport.

The person occupying the position of Service Manager - Data and Artificial Intelligence directs the technical integration, deployment, and production readiness capabilities required to operationalize AI products, models, and agents, as well as supporting data pipelines across Air Canada's enterprise environments. They ensure that AI solutions transition from approved technical architecture and design to development, testing, and production phases in a secure, controlled, repeatable, and increasingly automated manner. They lead AI systems integrators and Deployment specialists, establish reusable integration and deployment models, and work with AI engineering, data engineering, platform engineering, Architecture, Cybersecurity, Cloud operations, and Data operations teams to achieve sustainable production results. The person in this position must find a balance between engineering speed and enterprise governance, operational stability, traceability, and risk-based controls.

The position can be based in Montreal or Toronto.

Responsibilities:

• Lead AI systems integration and manage specialists responsible for transitioning AI solutions from approved designs to enterprise environments.
• Ensure that AI products, models, agents, and APIs and supporting data pipelines are properly integrated with enterprise platforms and upstream and downstream systems.
• Supervise the deployment and configuration of AI-related workloads across development, testing, and production environments.
• Drive infrastructure as code, integration and deployment pipelines, machine learning operations (MLOps) and large language model operations (LLMOps) models, including application and model promotion, release management, rollbacks, and environment management.
• Implement reusable integration models, deployment components, templates, and automation processes to reduce solution-specific engineering tasks and accelerate adoption.
• Collaborate with AI Product Managers, Data Scientists, AI Engineers, Solution Architects, Enterprise IT Architects, Cybersecurity, Cloud Operations, Platform Engineering, and Data Operations to translate designs into production-ready releases.
• Define and enforce production readiness criteria, including monitoring, logging, alerting, runbooks, support documentation, operational responsibilities, and recovery procedures.
• Ensure integrations and deployments meet architecture, cybersecurity, infrastructure, data governance, privacy, and operational requirements.
• Implement risk-based controls including appropriate human approval points for solutions involving sensitive data, AI models, autonomous agents, or important business decisions.
• Lead technical validation, go-live preparation, post-deployment verification, and orderly transition to stable operational support.
• Define and track success metrics for deployments, integration quality, automation, reliability, rework, and operational readiness.
• Identify recurring integration and deployment issues and improve upstream engineering practices, standards, and reusable tools.
• Manage demand, priorities, capacity, dependencies, and delivery commitments for the AI systems integration function.
• Lead, mentor, and develop a high-performing technical team, establish clear responsibilities, and support career advancement.
• Provide leadership during complex or high-risk implementations and act as a resource for escalations regarding integration and deployment issues.
• Manage relationships with technology partners and external vendors that complement internal delivery capabilities.
• Maintain up-to-date knowledge of engineering practices related to AI, cloud, integration, deployment, and production, and evaluate their applicability to Air Canada.

Qualifications

• University degree in computer science, engineering, information technology, or a related field, or equivalent work experience.
• At least seven years of technology experience at various levels, including at least three years in a technical team leadership position within a large and complex enterprise environment.
• Proven experience in systems integration, cloud engineering, platform engineering, development and operations, software delivery, or production activities.
• Excellent understanding of integration and deployment pipelines, Git source control, branching strategies, automated testing, infrastructure as code, deployment pipelines, and deployment across different environments.
• Practical knowledge of modern data and AI ecosystems, including Azure, Snowflake, Databricks, Azure DevOps or GitHub, orchestration platforms, and AI and machine learning deployment tools.
• Understanding of concepts related to machine learning operations (MLOps) and large language model operations (LLMOps), model and application deployment, version management, observability, and production lifecycle management.
• Experience with API integration, data pipelines, cloud services, identity and access controls, enterprise applications, and event-driven components.
• Excellent knowledge of enterprise practices regarding IT architecture, cybersecurity, change, release, and IT service management.
• Proven ability to balance governance, production risks and controls, with execution speed and automation.

Proven punctuality and reliability to promote overall team success in a fast-paced environment.Experience in an operationally critical position in the aviation or transportation sector, or another highly regulated sector, an asset.

Employment conditions:

Candidates must be eligible to work in the country concerned at the time a job offer is presented and are responsible for obtaining necessary work permits, visas, or other authorizations. Proof of eligibility must be provided before the start date.

Language Requirements

Equal skills being equal, 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 workplace that highlights the unique contribution of our employees to our company's success.

As an equal opportunity employer, we encourage diverse applications in order to build a workforce that is varied and representative of our customers and the communities where we live and offer our services.

Air Canada thanks all applicants for their interest, but only those selected for an interview will be contacted.