Azure AI DevOps Engineer
- Source: Naukri
- Tata Consultancy Services
- On-site
- Bengaluru
- Full-Time
- Mid level
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
- Azure DevOps
- CI/CD Pipelines
- Microsoft Azure
- Azure Machine Learning
- MLOps
- Terraform / IaC
- Docker
- Kubernetes / AKS
- Git
- Python / scripting
Good to Have
- Azure AI services
- MLflow
- Azure Container Registry
- Azure Monitor
- Key Vault
- Azure CLI
- GitHub Actions
- GenAI / LLM deployment exposure
Skills
- microsoft-azure
- azure-devops
- azure-machine-learning
- Terraform
- Docker
- Kubernetes
- azure-rbac
- Python
- ml-flow
- mlflow
- microsoft-azure-container-registry
- azure-monitor
- vault
- Github
- github-actions
