Technical Lead - Data and Artificial Intelligence

Belonging to Air Canada is akin to belonging to a Canadian symbol, 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 Technical Lead – Data and Artificial Intelligence acts as the technical lead responsible for the implementation, integration, and operation of Air Canada’s enterprise-grade agentic platform. Their role consists of translating the company’s AI strategy, architecture, governance, and business requirements into a modular, secure, observable, and reusable platform that enables the deployment and consistent operation of AI products and agentic solutions across the enterprise.

The immediate priority of the incumbent is to establish and integrate three foundational capabilities into the platform: the AI knowledge model, comprising enterprise knowledge graph, semantic, ontology, metadata, traceability, and retrieval models; AI observability and tracing, offering end-to-end visibility into the execution of agents, models, prompts, retrieval processes, and tools; and testing and evaluation capabilities, ensuring standardized pre-production testing, continuous production evaluation, quality controls, and data-driven release criteria. The successful candidate will collaborate with the Data and Artificial Intelligence, Enterprise Architecture, Cybersecurity, AI Governance, Digital Products, and Software and Platform Development teams, as well as external partners, to ensure these capabilities function as common enterprise services rather than isolated, platform-specific solutions.

Responsibilities:

• Ensure technical responsibility for the implementation, integration, operation, and evolution of the enterprise-grade agentic platform.
• Translate business, architecture, security, and governance requirements into technical designs, engineering product backlogs, and implementation milestones.
• Define platform architecture in collaboration with Enterprise Architecture, ensuring modularity, interoperability, scalability, security, and compliance with Air Canada standards.
• Integrate AI platforms, agent frameworks, gateways, registries, knowledge services, observability tools, and evaluation capabilities.
• Implement the AI knowledge model including knowledge graph, ontology, semantic, metadata, provenance, traceability, and retrieval models.
• Establish reusable and interconnected domain knowledge models that avoid monolithic or redundant knowledge layers.
• Implement distributed observability and tracing for all aspects involving agents, models, prompts, retrieval, tools, latency, errors, costs, security, and business outcomes.
• Define common standards for telemetry, instrumentation, traceability, sessions, dashboards, alerts, and diagnostics.
• Establish common testing and evaluation capabilities for pre-production testing, pre-release gates, regression and security tests, and continuous production evaluation.
• Establish models for evaluation datasets, synthetic tests, automated evaluators, deterministic checks, human reviews, quality thresholds, and evidence retention.
• Integrate testing, evaluation, observability, and quality controls into continuous integration and deployment pipelines and AI product lifecycle processes.
• Define technical acceptance criteria and validate platform capabilities, integrations, and partner deliverables.
• Develop reusable components, APIs, software development kits, templates, reference implementations, and infrastructure-as-code models.
• Support low-code, code-based, embedded, autonomous, and customized agentic solutions spanning multiple technologies.
• Collaborate with Cybersecurity, Identity and Access Management, AI Governance, Privacy, Risk Management, and Architecture teams to implement secure, auditable, and responsible AI controls.
• Collaborate with Cloud, Infrastructure, Network, DevOps, and Platform teams to build and operate required environments and services.
• Monitor and optimize platform reliability, performance, scalability, availability, resource utilization, and costs.
• Lead incident investigations, root cause analyses, and the implementation of corrective measures for common platform functionalities.
• Maintain the technical roadmap, architectural decisions, integration standards, operational documentation, and support procedures.
• Provide technical guidance to internal teams, contractors, and partners while fostering integration, knowledge transfer, mentoring, and sustainable internal ownership.

Qualifications

• Degree in Engineering, Computer Science, or Mathematics and Statistics.
• At least five years of experience in AI, software, data, cloud, or platform engineering within a large enterprise.
• Experience leading the design, implementation, integration, or operation of enterprise platforms and common services.
• Strong knowledge of agentic AI, generative AI, large language models, orchestration, retrieval-augmented generation, tool integration, and AI product lifecycle practices.
• Knowledge of Azure, AWS, Snowflake, and other AI-driven platforms.
• Experience with knowledge graphs, ontologies, semantic models, metadata, traceability, or knowledge management.
• Knowledge of AI observability, telemetry, distributed tracing, monitoring, diagnostics, performance, and cost management.
• Experience in AI testing and evaluation, including evaluation datasets, automated evaluation, regression testing, security testing, human review, and release gates.
• Strong knowledge of cloud-native architecture, APIs, identity and access management, CI/CD pipelines, infrastructure as code, cybersecurity, and responsible AI.
• Proven ability to exercise good judgment, attention to detail, and determination in solving complex problems.
• Proven ability to gather, manage, and summarize large amounts of information efficiently, thoroughly, and creatively.
• Ability to work collaboratively within a team and drive cross-team solutions with complex interdependencies and requirements.
• Strong oral and written communication, interpersonal, and research skills, exceptional time management and organizational skills, and proven ability to be highly productive and effective in a team environment.
• Excellent analytical and problem-solving skills.
• Experience managing AI platforms for airlines, an asset.
• Demonstrate punctuality and reliability to support the overall success of the team in a fast-paced environment.

Personal Qualities

• Combine deep, hands-on technical expertise with a global vision of the enterprise platform.
• Inspire and energize engineering teams by showing great enthusiasm and fostering a culture of excellence and accountability.
• Demonstrate an innovative and forward-looking mindset, constantly exploring emerging technologies and non-traditional solutions to tackle complex challenges.
• Establish and maintain a culture of trust, transparency, and psychological safety to enable open dialogue that fosters diverse perspectives.
• Challenge assumptions and the status quo with curiosity and courage to drive continuous improvement and team performance.
• Promote interoperability, reusability, standardization, security, and sustainable engineering practices.
• Lead by example through integrity, resilience, and a commitment to mentoring colleagues to reach their full potential.
• Demonstrate initiative, good judgment, curiosity, and rigorous execution.

Employment Conditions:

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

Linguistic 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 the success of our company.

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

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