Description
A results-driven AI Engineer with solid DevOps and Cloud Engineering expertise to support the design, deployment, and operation of scalable, production-grade AI and data platforms on Microsoft Azure. The ideal candidate brings hands-on experience working at the intersection of DevOps, cloud infrastructure, and machine learning enablement, with a transparent focus on automation, reliability, and secure delivery.

Responsibilities
Key Responsibilities
Build, manage, and optimize CI/CD pipelines using Azure DevOps and GitHub Actions for AI, data, and application workloads.
Deploy and operate AI-enabled and data platforms on Azure Kubernetes Service (AKS) using Docker and Helm.
Provision and manage Azure infrastructure including compute, networking, storage, and security services.
Enable MLOps and data pipelines by supporting ETL workflows using Azure Data Factory and Databricks.
Implement secure configuration and secrets management using Azure Key Vault.
Monitor platform health, performance, and availability using Azure Monitor and Log Analytics.




Conduct performance and load testing using JMeter / BlazeMeter and drive optimization actions.
Collaborate with ML engineers to support model packaging, versioning, deployment, and monitoring in production.
Support Agile delivery through automation, release coordination, and continuous improvement.
Track and optimize cloud infrastructure costs across settings.

Qualifications
3 to 6 years of relevant experience in AI platform enablement, DevOps, Cloud Engineering, or related roles
Proven experience supporting production workloads on Microsoft Azure
Hands-on exposure to CI/CD automation, container platforms, and cloud-native architectures

Education
Bachelor’s degree required (Engineering, Computer Science, or related discipline preferred)
Technical Skills
Azure DevOps Pipelines and GitHub Actions
YAML-based CI/CD automation
Azure Kubernetes Service (AKS)
Docker and Helm
Azure

📌 Manager Ai Engineering Bengaluru
🏢 EXL
📍 Bengaluru