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Our client is looking for an Intermediate DevOPS/Cloud Engineer for a 6 month contract in Toronto. This is a hybrid role. Rate: $65.74 - $72.13
Job Responsibility:
Design, build, and maintain CI/CD pipelines to enable fast, reliable, and repeatable software delivery across development, staging, and production environments.
Collaborate with development teams to integrate automated testing, code quality gates, and deployment approvals into pipeline workflows.
Identify bottlenecks in the delivery process and implement automation solutions to reduce manual effort and increase deployment frequency.
Maintain pipeline-as-code standards and ensure version-controlled, auditable pipeline configurations across the organization.
Develop and maintain cloud infrastructure using IaC tools (e.g., Terraform, Bicep, or ARM templates) to ensure consistent, repeatable provisioning across environments.
Enforce infrastructure standards and best practices through code reviews, modular templating, and reusable component libraries.
Collaborate with architecture and data engineering teams to translate infrastructure requirements into well-structured, scalable IaC implementations.
Lead remediation of infrastructure drift and maintain alignment between declared and actual cloud state.
Provision, configure, and manage Databricks, Azure AI and ML infrastructure including Azure Machine Learning workspaces, Azure OpenAI Service, Cognitive Services, and AI Foundry resources.
Collaborate with data science and engineering teams to build and maintain CI/CD pipelines for model training, evaluation, and deployment workflows.
Implement governance and access controls for AI resource consumption, including quota management, endpoint security, and cost tagging specific to AI workloads.
Ensure AI infrastructure is deployed using IaC principles and integrated with broader platform standards for observability, networking, and compliance.
Stay current with Azure AI platform updates and evaluate new services to support evolving business requirements around AI/ML delivery.
Implement and maintain monitoring, alerting, and logging solutions to ensure full observability across applications and infrastructure (e.g., Elastic, ).
Define SLIs, SLOs, and alerting thresholds in collaboration with development and operations teams.
Lead incident response efforts by leveraging observability tooling to triage, diagnose, and resolve issues efficiently.
Continuously improve dashboards, runbooks, and on-call processes to reduce Mean Time to Resolution (MTTR).
Requirements:
3+ years experience: Design, build, and maintain CI/CD pipelines to enable fast, reliable, and repeatable software delivery across development, staging, and production environments.
3+ years experience: Develop and maintain cloud infrastructure using IaC tools (e.g., Terraform, Bicep, or ARM templates) to ensure consistent, repeatable provisioning across environments.
3+ years experience: Provision, configure, and manage Databricks, Azure AI and ML infrastructure including Azure Machine Learning workspaces, Azure OpenAI Service, Cognitive Services, and AI Foundry resources.
3+ years experience: Implement and maintain monitoring, alerting, and logging solutions to ensure full observability across applications and infrastructure (e.g., Elastic, ).