Azure DevOps Engineer

DevOps Engineer – Azure | Terraform | AKS | Databricks | MLOps

Experience: 5–10 Years

Location: Remote - India

Engagement: Contract

Duration: 6 months, with possibility of extension

About the Role

We are looking for an experienced DevOps Engineer with strong hands-on expertise in Azure cloud infrastructure, CI/CD automation, Infrastructure as Code, and container orchestration. The ideal candidate will support application, data, and AI workloads by building secure deployment pipelines, automating infrastructure, and improving production reliability. Experience with Databricks CI/CD, MLOps, and LLMOps will be valuable.

Key Responsibilities

• Design, implement, and manage CI/CD pipelines for application, data, and AI workloads using Azure DevOps and GitHub Actions.
• Automate the deployment of Azure services, Databricks assets, and cloud infrastructure.
• Implement Infrastructure as Code (IaC) using Terraform, Bicep, and ARM templates.
• Configure monitoring, observability, logging, and alerting to ensure system reliability and performance.
• Support MLOps and LLMOps workflows, including AI model deployment and automation.
• Implement security controls, secrets management, access policies, and compliance standards.
• Manage containerised applications and Kubernetes environments using Docker and Azure Kubernetes Service (AKS).
• Support production releases, incident response, troubleshooting, and reliability engineering.
• Automate operational processes using Python, PowerShell, and Bash scripting.
• Collaborate with development, data engineering, AI/ML, and security teams to improve deployment efficiency and operational stability.

Required Skills and Technologies

• Cloud & CI/CD: Microsoft Azure, Azure DevOps, GitHub Actions.
• Infrastructure as Code: Terraform, Bicep, ARM Templates.
• Containers & Orchestration: Docker, Kubernetes, Azure Kubernetes Service (AKS).
• Monitoring & Observability: Azure Monitor, Log Analytics, Application Insights.
• Databricks: Databricks Asset Bundles, automated deployment, and CI/CD pipelines.
• AI/ML Operations: MLflow, MLOps, LLMOps concepts, and AI deployment automation.
• Scripting: Python, PowerShell, Bash.
• Security & Governance: Role-Based Access Control (RBAC), Azure Key Vault, secrets management, and Azure Policy.
• Production Operations: Release management, incident response, troubleshooting, and reliability engineering.