Principal Platform Architect – AI and Data Platforms

Canadian Tire Corporation

. Play a pivotal leadership role within the Enterprise AI and Emerging Technology team .

Posted 5/7/2026full-timeToronto • 🇨🇦 CanadaLeadWebsite

Tech Stack

Tools & technologies

AWSAzureCloudDockerETLGoogle Cloud PlatformHadoopKubernetesSparkTerraformUnity

About the role

Key responsibilities & impact

Play a pivotal leadership role within the Enterprise AI and Emerging Technology team
Responsible for shaping and executing the organization’s strategy across AI, Data Platforms, and Data Governance (DG)
Define and drive the end-to-end architecture vision
Lead the design and implementation of scalable AI and data solutions
Establish governance and standards
Guide large-scale transformation initiatives
Work closely with stakeholders across business and technology teams
Build future-ready AI and data ecosystems
Lead architectural practices and mentor teams
Define and evolve the AI and Data Platform architecture strategy and roadmap
Develop and maintain architecture models, standards, and roadmaps
Lead enterprise-wide solution blueprints covering data platforms, AI pipelines, BI, and governance capabilities
Design modern data platforms (e.g., Lakehouse architectures, data engineering pipelines, BI/reporting ecosystems)
Architect scalable AI/ML systems leveraging cloud platforms such as Azure or GCP
Enforce AI, data, and architecture governance standards
Contribute to the evolution of enterprise architecture frameworks, practices, and processes
Lead architecture reviews and govern solution design through project lifecycle gates
Partner with business and technology stakeholders to translate requirements into architecture solutions
Present architectural strategies and solutions to senior leadership and executive stakeholders
Advocate for enterprise architecture practices and promote technology standardization and reuse
Lead and mentor architecture team members and contribute to capability growth
Drive continuous improvement in engineering practices, performance optimization, and solution quality
Foster a culture of innovation, collaboration, and technical excellence across AI and data domains

Requirements

What you’ll need

5–10+ years of experience in enterprise architecture, data platforms, or AI/ML solutions
Proven experience delivering large-scale, complex solutions across AI and data ecosystems
Agentic AI experience (Tool Usage, Agentic Orchestration Frameworks, LLMs, Testing and Evaluation, AgentOps)
GenAI (LLMs, Monitoring, Testing and Evaluation, LLMOps, Observability, RAG)
Data platforms & lakehouse architectures (e.g., ADLS Gen2, Databricks, Synapse, ETL/ELT, Unity Catalog)
MLOps technologies (ML, NLP)
Cloud platforms (Azure preferred; AWS/GCP knowledge beneficial)
Big data technologies (e.g., Spark, Hadoop)
DevOps & CI/CD practices, Infrastructure as Code (Terraform, etc.)
Containerization and orchestration (Docker, Kubernetes)
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (PhD considered an asset)

Benefits

Comp & perks

Competitive salaries and wages
Store discounts
Supported learning through our Triangle Learning Academy
Canadian Tire Profit Sharing
Retirement and savings programs for eligible employees
Mental health benefits in the amount of $5,000 per year for benefits-eligible employees and their families, including total well-being, and mental health tools and resources for all employees

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

enterprise architectureAI solutionsdata platformsAI/ML systemslakehouse architecturesMLOpsbig data technologiesDevOpsCI/CD practicescontainerization

Soft Skills

leadershipmentoringcollaborationinnovationcommunicationstakeholder engagementstrategic thinkingproblem-solvingcontinuous improvementgovernance

Certifications

Bachelor's degreeMaster's degreePhD