Azure AI with DevOps - S

Tata Consultancy Services; Hyderabad, Chennai, Bengaluru; On-site; INR 1,500,000 - 2,400,000; Full time

Job summary

Tata Consultancy Services Limited in India seeks an experienced Azure MLOps Engineer to design, build, and deploy AI/ML solutions using Azure AI services. You will implement end-to-end MLOps pipelines for training, validation, deployment, and monitoring, and automate infrastructure using Terraform, ARM, or Bicep.

You will work with AKS, Azure ML, and OpenAI integrations while ensuring security, governance, and cost optimization across Azure environments.

Qualifications

• Proven experience with Microsoft Azure cloud platform and AI services.
• Hands-on experience with Azure ML, OpenAI Service, and AI search capabilities.
• Proficiency in Python, Java or C# for AI/ML solutions.
• Strong knowledge of CI/CD and MLOps practices.
• Experience with Docker, Kubernetes, and Infra as Code (Terraform, ARM/Bicep).
• Familiarity with Git and RESTful APIs; ability to design scalable services.

Responsibilities

• Design, develop, and deploy AI/ML solutions using Azure AI services.
• Build end-to-end MLOps pipelines for training, validation, deployment, and monitoring.
• Implement CI/CD pipelines using Azure DevOps, GitHub Actions, or similar tools.
• Automate infrastructure provisioning with IaC tools like Terraform or ARM/Bicep.
• Deploy AI workloads on AKS, Azure Container Apps, and Azure ML.
• Integrate Azure AI capabilities into enterprise applications.
• Monitor performance, model accuracy, and infrastructure health.
• Ensure security, governance, and cost optimization across Azure environments.
• Collaborate with cross-functional teams to translate business requirements.
• Troubleshoot deployment and operational issues across cloud/AI environments.

Skills

Azure cloud platform

CI/CD pipelines

MLOps concepts

REST APIs

Docker

Kubernetes

Python

Java/C#

Tools

Azure Machine Learning

Azure OpenAI Service

AKS (Azure Kubernetes Service)

Terraform

Terraform/Azure IaC

Job description

Key Responsibilities

• Design, develop, and deploy AI/ML solutions using Microsoft Azure AI services.
• Build and manage end-to-end MLOps pipelines for model training, validation, deployment, and monitoring.
• Implement CI/CD pipelines using Azure DevOps, GitHub Actions, or similar tools.
• Automate infrastructure provisioning using Infrastructure as Code (IaC) tools such as Terraform, ARM Templates, or Bicep.
• Deploy and manage AI workloads on Azure Kubernetes Service (AKS), Azure Container Apps, and Azure Machine Learning.
• Integrate Azure OpenAI, Cognitive Services, Azure AI Search, and other Azure AI capabilities into enterprise applications.
• Monitor application performance, model accuracy, and infrastructure health using Azure Monitor, Log Analytics, and Application Insights.
• Ensure security, compliance, governance, and cost optimization across Azure environments.
• Collaborate with cross-functional teams to translate business requirements into scalable AI solutions.
• Troubleshoot deployment, performance, and operational issues across cloud and AI environments.

Required Skills & Qualifications

• Strong experience with Microsoft Azure cloud platform.
• Hands-on experience with:
• Azure Machine Learning
• Azure OpenAI Service
• Azure AI Search
• Azure Cognitive Services
• Azure Kubernetes Service (AKS)
• Azure Functions
• Azure Container Registry (ACR)
• Azure Storage Services
• Experience with Azure DevOps and CI/CD pipeline implementation.
• Proficiency in Python, C#, or Java.
• Knowledge of Docker and Kubernetes.
• Experience with Infrastructure as Code (Terraform, Bicep, ARM Templates).
• Familiarity with Git version control systems.
• Understanding of MLOps concepts and AI model lifecycle management.
• Knowledge of REST APIs and microservices architecture.
• Experience with monitoring and observability tools.