Senior devops engineer (noida)– azure cloud transformation & ai automation

Senior Dev Ops Engineer (Noida)– Azure Cloud Transformation & AI Automation - Immediate Joiner

Senior Dev Ops Engineer – Azure Cloud Transformation & AI Automation (Noida Hybrid- EST Time)

Overview

We are seeking an experienced Senior Dev Ops Engineer with deep expertise in Microsoft Azure, Infrastructure as Code (Ia C), CI/CD automation, and Azure AI technologies. In this role, you will take ownership of designing, implementing, validating, and automating Azure Landing Zone deployments, cloud migrations, and AI platform provisioning, enabling scalable and secure enterprise cloud solutions. The ideal candidate has hands-on experience with Azure migrations, Dev Ops automation, Azure AI Foundry, and AI model deployment, with a strong focus on reliability, governance, and operational excellence.

Key Responsibilities

• Design, implement, and automate Azure Landing Zone (Hub & Spoke) deployments, including networking, firewall and NSG configurations, governance policies, and monitoring solutions.

• Implement Infrastructure-as-Code (Ia C) using Terraform, Bicep, and ARM templates.

• Build, migrate, and optimize CI/CD pipelines using Azure Dev Ops and Git Hub Actions for infrastructure, applications, databases, and platform services.

• Integrate validation processes including linting, security scanning, automated deployment testing, and compliance checks.

• Develop automated deployment, rollback, and disaster recovery procedures.

• Create migration runbooks and automate migration processes for enterprise workloads.

• Automate provisioning and migration of databases into Azure SQL Managed Instance.

• Support wave-based migration execution using Azure Migrate, Azure Site Recovery (ASR), and database migration tools.

• Perform automated post-migration validation, including networking, SSL, backup verification, performance testing, and database integrity assessments.

• Design and automate Azure AI Foundry provisioning and configuration using Infrastructure-as-Code and CI/CD pipelines.

• Automate deployment and lifecycle management of AI models, Azure AI Foundry projects and environments, and AI agents.

• Implement deployment pipelines for self-hosted and custom-hosted AI models within Azure AI Foundry.

• Establish governance, monitoring, and security controls for AI workloads and model deployments.

• Create and maintain comprehensive documentation for pipelines, infrastructure, migration runbooks, and troubleshooting procedures.

Required Skills & Experience

• 5+ years of professional experience as a Dev Ops Engineer, preferably supporting Azure migration, cloud transformation, or modernization initiatives.

• Microsoft Azure Certified.

• Strong expertise with Azure Dev Ops and/or Git Hub Actions.

• Hands-on experience with Terraform, Bicep, and ARM templates.

• Deep understanding of Azure Landing Zone (Hub & Spoke) architecture, deployment, validation, and automation.

• Experience with Azure AI Foundry provisioning, model deployment automation, and AI agent deployment, including support for self-hosted and custom-hosted models.

• Experience designing and automating CI/CD pipelines for AI and machine learning workloads.

• Practical experience migrating SQL Server, Oracle, or Postgre SQL workloads into Azure SQL Managed Instance.

• Strong scripting and automation skills using Power Shell, Python, and/or Bash.

• Familiarity with validation frameworks, security scanning, automated testing, and compliance automation.

• Excellent troubleshooting, communication, documentation, and stakeholder management skills.

Nice to Have

• Experience with Azure Monitor, Application Insights, and Splunk.

• Knowledge of Policy-as-Code, governance automation, and security validation within CI/CD pipelines.

• Experience with enterprise-scale, wave-based migration programs and cutover activities.

• Understanding of Fin Ops practices and Azure cost optimization strategies.

• Exposure to MLOps practices, model lifecycle management, and AI governance frameworks.

• Experience with containerized AI workloads, Kubernetes, and Azure-native AI services.