Artificial Intelligence Engineer

EXL; Bengaluru; On-site; INR 1,200,000 - 2,200,000; Full time

Job summary

EXL is seeking an AI Engineer with strong DevOps and Cloud engineering expertise to design, deploy, and operate scalable AI and data platforms on Microsoft Azure. The role emphasizes automation, reliability, and secure delivery while collaborating with application, data, and ML teams in an Agile environment.

The candidate will build CI/CD pipelines, deploy on AKS with Docker and Helm, provision Azure infrastructure, enable MLOps with Data Factory and Databricks, and monitor health with Azure

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.

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 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 environments.

Skills

Azure DevOps

GitHub Actions

CI/CD YAML

Docker

Helm

Azure Data Factory

Databricks

Azure Monitor

Log Analytics

Bash

PowerShell

Python

Education

Bachelor's degree

Tools

AKS

Job description

We are looking for a results-driven AI Engineer with strong 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 clear focus on automation, reliability, and secure delivery.

This role partners closely with application, data, and machine learning teams to ensure AI solutions are deployed efficiently, monitored effectively, and operated at scale in an Agile environment.

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 environments.

Required Technical Skills

• Azure DevOps Pipelines and GitHub Actions
• YAML-based CI/CD automation
• Docker and Helm
• Azure Data Factory and Databricks
• Azure Monitor and Log Analytics
• Bash, PowerShell, Python (basic)

Professional Skills

• Strong problem-solving and analytical mindset
• Excellent collaboration and stakeholder communication skills
• Experience working in Agile / Scrum teams
• High ownership, accountability, and execution focus
• Ability to work across DevOps, data, and AI engineering domains
• Continuous improvement and automation-first mindset

Experience

• 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)