As an AI ModelOps Engineer, you will be part of the Enterprise AI Platforms & AI ModelOps team within the AI and Data group at Canadian Tire Corporation (CTC). In this role, you will support the infrastructure and provisioning of environments that enable AI teams to build and deploy agentic AI solutions. You will help design, implement, operate, and optimize the platforms, tools, and processes that support AI solutions across their lifecycle.You will contribute to the evolution of CTC's AAAI platform and MLOps ecosystem, enabling the development, deployment, monitoring, and governance of machine learning solutions at scale. You will also help establish and mature CTC's Agentic AI platform capabilities, including support for generative AI, large language models (LLMs), AI agents, agentic workflows, and emerging AI engineering practices.ResponsibilitiesDesign, implement, operate, and continuously improve platforms, tools, and processes supporting the end-to-end lifecycle of AI solutionsEnable deployment, monitoring, governance, and lifecycle management of ML models, generative AI solutions, and AI agents in productionContribute to the evolution and operational excellence of CTC's AAAI platform and MLOps ecosystemHelp establish and mature Agentic AI platform capabilities including infrastructure, tooling, registries, observability, and evaluation frameworksDevelop and maintain automation, CI/CD pipelines, and platform services that accelerate delivery of AI solutionsDesign and implement observability, monitoring, alerting, and troubleshooting capabilities for AI platformsCollaborate with data scientists, AI engineers, cloud engineers, architects, and IT teamsEvaluate, recommend,



and implement emerging AI platform technologies and engineering practicesSupport platform governance including model and agent lifecycle management, auditability, and responsible AI practicesContribute to platform standards, reusable components, reference architectures, and best practicesEnsure availability, scalability, resilience, security, and cost efficiency of AI platform infrastructurePerform post-deployment analysis and operational reviewsStay current with industry trends in ML, generative AI, Agentic AI, and cloud platformsRequirementsHands-on experience with MLOps, GenAI operations, or AI platform engineeringExperience building and operating AI, ML, or data platforms in cloud environments, preferably Microsoft AzureStrong understanding of machine learning concepts, model lifecycle management, and governanceExperience with generative AI, LLMs, RAG, AI agents, and emerging AI engineering practicesProficiency in Python and experience developing AI-enabled applicationsExperience with Azure AI Foundry, Azure Machine Learning, Databricks, MLflow, or similar platformsExperience with containerization: Docker, Kubernetes, and related orchestration platformsFamiliarity with DevOps practices including CI/CD pipelines, source control, automation, and IaCPractical experience with Terraform, Bicep, or equivalent IaC toolsKnowledge of cloud security, governance, access management, and responsible AI practicesExcellent verbal and written communication skillsBachelor's degree in Computer Science, Engineering, Information Technology, or related disciplineBachelor's degree in Computer Science, Engineering, Information Technology, or related discipline, or equivalent combination of education, certifications, and experience. Hands-on MLOps or AI platform engineering experience. Proficiency in Python. Experience with Azure, Docker, Kubernetes, Terraform or Bicep, and AI platforms such as Azure AI Foundry or Databricks.

📌 Ai Modelops Engineer (Toronto)
🏢 Canadian Tire Corporation
📍 Toronto