Azure Cloud Engineer

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.