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Salary
≈ $12k – $28k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Middle · 3+ years exp

Confirmed on the employer's own hiring board on Oct 22, 2026. First seen by Alion on May 19, 2026. EXL scores B on the Alion truth index.

Overview
Company
Impact
Profile match

EXL

EXL, legally ExlService Holdings, is a data analytics, AI and digital operations company headquartered in New York that runs outsourced business processes and builds data and AI solutions for insurers, healthcare organisations, banks, media and retail companies. Founded in 1999 and listed on Nasdaq, it has more than 60,000 employees across six continents, with large delivery centers in Noida, Gurgaon, Pune, Bengaluru and Chennai and a newer AI hub in Dublin. It hires data scientists and data engineers, GenAI and MLOps engineers, analytics managers, solution consultants and client partners, plus talent acquisition, finance and medical coding staff.

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.

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.
  • 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 App Service, Virtual Machines, VNet
  • Azure Data Lake Storage (ADLS Gen2)
  • Azure SQL Database
  • Azure Container Registry (ACR)
  • Azure Key Vault
  • 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

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