Senior Azure Devops Engineer

Job Description: DevOps Engineer (Azure)

Experience: 3–6 Years

Salary: ₹15–25 LPA

Location: Remote (Work from Home)

Employment Type: Full-time

About the Role

We are looking for an experienced DevOps Engineer with strong hands-on expertise in Microsoft Azure, Terraform, Kubernetes, and Docker. The ideal candidate will have proven experience deploying, managing, and scaling production-grade systems on Azure.

You will be responsible for building and maintaining cloud infrastructure, automating deployments, improving system reliability, and developing efficient infrastructure automation workflows using Python, Bash, and modern AI coding tools such as Claude and OpenAI Codex.

Key Responsibilities

• Design, deploy, and manage scalable, highly available production infrastructure on Microsoft Azure.
• Build and maintain Infrastructure as Code (IaC) using Terraform, including reusable modules, remote state management, workspaces, and variables.
• Manage multi-environment Azure infrastructure, including development, staging, and production.
• Deploy, configure, and maintain containerized applications using Docker and Kubernetes.
• Develop and maintain CI/CD pipelines for automated builds, testing, and deployments.
• Write Python scripts and Bash scripts to automate infrastructure provisioning, monitoring, deployment, and operational tasks.
• Monitor system performance, troubleshoot production issues, and improve reliability, scalability, and security.
• Implement cloud infrastructure best practices for access management, networking, cost optimization, and disaster recovery.
• Leverage AI coding tools such as Claude and OpenAI Codex to accelerate scripting, infrastructure development, debugging, and automation.
• Collaborate with engineering teams to improve deployment processes and operational efficiency.

Mandatory Skills

• Microsoft Azure: Strong hands-on production experience with Azure cloud infrastructure.
• Terraform: Practical experience creating modules, managing remote state, variables, workspaces, and multi-environment infrastructure.
• Kubernetes: Experience deploying and managing containerized applications and scalable workloads.
• Docker: Hands-on experience building, managing, and deploying container images.
• Python: Strong scripting and automation skills.
• Bash Scripting: Ability to automate infrastructure and operational workflows.
• Scalable Systems: Proven experience deploying and managing scalable, production-grade systems.

Required Experience

• 3–6 years of experience in DevOps engineering, with significant hands-on experience in Azure production environments.
• Demonstrated experience deploying and scaling real-world applications in production.
• Strong understanding of cloud networking, infrastructure automation, CI/CD, monitoring, and troubleshooting.
• Experience using AI coding assistants such as Claude or OpenAI Codex for development and automation is highly desirable.

Preferred Qualifications

• Experience with Azure Kubernetes Service (AKS).
• Familiarity with Azure Monitor, Log Analytics, and cloud observability tools.
• Understanding of cloud security, secrets management, and identity and access management.
• Experience with Git-based workflows and CI/CD tools such as Azure DevOps or GitHub Actions.
• Experience optimizing cloud infrastructure for performance, reliability, and cost.

What We’re Looking For

• A hands-on engineer who has independently deployed and managed scalable production systems.
• Strong problem-solving and debugging skills.
• Ability to take ownership of cloud infrastructure and automation tasks.
• Someone comfortable working independently in a remote environment.
• A practical mindset focused on automation, reliability, and continuous improvement.

Important: Candidates must have strong hands-on experience with Azure, Terraform, Kubernetes, and Docker, along with a proven track record of deploying scalable production systems.

How to Apply

Interested candidates can share their updated resume along with details of their Azure, Terraform, Kubernetes, and production deployment experience.