Azure AI DevOps Engineer

Tata Consultancy Services; Hyderabad, Chennai District, Bengaluru; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

Tata Consultancy Services is seeking an experienced Azure AI DevOps / MLOps Engineer to design, implement, and maintain CI/CD and MLOps pipelines for cloud, AI, and ML workloads. Expertise in Azure DevOps, Azure ML, and Terraform is required for production deployments.

Role involves collaborating with data scientists and cloud architects, deploying containerized apps with Docker/Kubernetes, and ensuring secure, monitored ML systems across environments.

Qualifications

• 8-10 years of hands-on experience in Azure DevOps and MLOps environments.
• Strong expertise in designing and implementing CI/CD pipelines for cloud AI/ML workloads.
• Proven experience with Azure ML and production AI/ML deployments.
• Infrastructure as Code using Terraform and cloud provisioning automation.

Responsibilities

• Design and manage CI/CD pipelines using Azure DevOps.
• Build automated MLOps pipelines with Azure Machine Learning for model training and deployment.
• Automate provisioning of Azure infrastructure using Terraform / IaC.
• Manage model deployment, versioning and production monitoring.
• Implement source control and branching strategies using Git.
• Containerize AI/ML applications using Docker and support Kubernetes-based deployments.
• Manage Azure security, authentication, RBAC and service connections.
• Implement monitoring, logging and troubleshooting for production workloads.
• Collaborate with Data Scientists, AI Engineers, Cloud Architects and DevOps teams.

Skills

Azure DevOps

CI/CD Pipelines

Microsoft Azure

Azure Machine Learning

MLOps

Terraform / IaC

Docker

Kubernetes / AKS

Git

Python / scripting

Tools

Docker

Kubernetes

Terraform

Git

Azure CLI

Job description

Role- Azure AI DevOps / MLOps Engineer

Experience: 8-10 Years

Location- Pan India

Job Description-

We are looking for an experienced Azure AI DevOps / MLOps Engineer to design, implement, and maintain CI/CD and MLOps pipelines for cloud, AI, and Machine Learning workloads. The candidate should have strong Azure DevOps experience along with hands-on knowledge of Azure Machine Learning and production AI/ML deployments.

Roles & Responsibilities

• Design and manage CI/CD pipelines using Azure DevOps.
• Build automated MLOps pipelines with Azure Machine Learning for model training and deployment. [learn.microsoft.com], [learn.microsoft.com]
• Automate provisioning of Azure infrastructure using Terraform / Infrastructure as Code.
• Manage model deployment, versioning and production monitoring.
• Implement source control and branching strategies using Git.
• Containerize AI/ML applications using Docker and support Kubernetes-based deployments where required.
• Manage Azure security, authentication, RBAC and service connections.
• Implement monitoring, logging and troubleshooting for production workloads.
• Collaborate with Data Scientists, AI Engineers, Cloud Architects and DevOps teams.
• Support deployment automation across development, testing and production environments.

Mandatory Skills

1. Azure DevOps
2. CI/CD Pipelines
3. Microsoft Azure
4. Azure Machine Learning
5. MLOps
6. Terraform / IaC
7. Docker
8. Kubernetes / AKS
9. Git
10. Python / scripting

Good to Have

• Azure AI services
• MLflow
• Azure Container Registry
• Azure Monitor
• Key Vault
• Azure CLI
• GitHub Actions
• GenAI / LLM deployment exposure