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Devops engineer • pickering on
Azure Cloud Engineer
VDart IncScarborough, ON, CanadaLead Software Engineer Developer
Cpus Engineering Staffing Solutions Inc.Pickering, ON, CAElectrical Engineer
AECOMPickering, Ontario, CanadaProject Engineer
Candevcon LimitedWhitby, Durham Region, CAFull Stack.Net Engineer
ComTEK Solutions, LLCAjax, ON, CAIAM Solutions Engineer
Global Technical TalentScarborough, ONRFP 25-176 Microsoft PowerApps Consultant 16 month contract Oshawa hybrid remote
CorGTAPickering, Ontario, CanadaOPEN : FinOps Engineer
CPUS Engineering Staffing Solutions Inc.PickeringDevOps Engineer Co-op
Procor LimitedOntario, CA25-125 FinOps Engineer
Morson TalentPickeringSecurity Engineer
Motion Recruitment Partners LLCWhitby, Durham Region, CASoftware Development Engineer II
Solera CorporationAjax, ON, CA- New!
Bash / PowerShell Engineer
SuperAnnotateAjax, Ontario, CARelease & Deployment Lead
Portfolio+Whitchurch-Stouffville, ON, CASecurity Engineer
Motion RecruitmentWHitby, Ontario, CanadaOPEN : FinOps Engineer
Rodan Energy SolutionsPickering, CASoftware Developer
VencoraWhitchurch-Stouffville, ON, CAElectrical Engineer
AecomPickering, ON, CAProject Engineer
Bird ConstructionAjax, Ontario, Canada- Oakville, ON (from $ 150,997 to $ 171,000 year)
- White Rock, BC (from $ 152,777 to $ 170,625 year)
- Surrey, BC (from $ 102,817 to $ 168,150 year)
- Kitchener, ON (from $ 96,559 to $ 167,375 year)
- Sherwood Park, AB (from $ 151,829 to $ 165,750 year)
- Fort St. John, BC (from $ 125,000 to $ 165,263 year)
- Thunder Bay, ON (from $ 126,750 to $ 165,000 year)
- North York, ON (from $ 124,164 to $ 165,000 year)
- St. Thomas, ON (from $ 153,000 to $ 165,000 year)
- East York, ON (from $ 124,164 to $ 165,000 year)
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Azure Cloud Engineer
VDart IncScarborough, ON, Canada- Full-time
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Job Title : Azure Cloud Engineer
Location : Scarborough, ON
Duration : Contract
Job Summary :
We are seeking an experienced Cloud Azure Engineer with strong expertise in CI / CD pipeline automation, application development, and a solid understanding of AI / ML integration within cloud environments.
The ideal candidate will design, implement, and manage scalable Azure cloud solutions, ensuring seamless deployment and operational excellence while enabling AI-driven innovations.
Key Responsibilities :
Cloud Infrastructure & Deployment
Design, implement, and maintain Azure cloud infrastructure using best practices for scalability, security, and cost optimization.
Automate provisioning and configuration using Azure DevOps, Terraform, or ARM templates.
CI / CD Pipeline Management :
Build, maintain, and optimize CI / CD pipelines for seamless integration and delivery across environments.
Implement continuous testing, monitoring, and deployment using Azure DevOps, GitHub Actions, or Jenkins.
Ensure smooth code deployments and rollback mechanisms with version control (Git).
Coding & Development :
Develop and maintain scripts, automation tools, and integrations using Python, PowerShell, or C#.
Collaborate with developers to containerize and deploy applications using Docker and Kubernetes (AKS).
AI & Data Integration :
Support integration of AI / ML models into cloud-based applications using Azure Machine Learning, Cognitive Services, or OpenAI Service.
Work closely with data and AI teams to enable secure model deployment and monitoring in production.
Monitoring & Security :
Implement monitoring, alerting, and performance optimization using Azure Monitor, Log Analytics, and Application Insights.
Ensure compliance with security standards, manage access control, and enforce DevSecOps best practices.
Required Skills & Qualifications :
Bachelor's degree in Computer Science, Engineering, or related field.
6+ to 9 years of experience in Azure Cloud Engineering or related roles.
Hands-on experience with Azure DevOps, CI / CD pipelines, and Infrastructure as Code (IaC).
Strong scripting / coding skills in Python, PowerShell, or C#.
Familiarity with Docker, Kubernetes, and microservices architecture.
Understanding of AI / ML workflows and tools (Azure ML, Cognitive Services, APIs).
Experience with monitoring, logging, and troubleshooting in cloud environments.
Preferred Qualifications :
Azure certifications (e.g., AZ-104, AZ-204, or AZ-400).
Experience integrating AI models into production environments.
Exposure to GitOps and DevSecOps methodologies.
Knowledge of REST APIs, event-driven architectures, and serverless computing (Azure Functions, Logic Apps).
Soft Skills :
Strong analytical and problem-solving skills.
Excellent communication and collaboration abilities.
Ability to work in an agile, fast-paced environment.