E
EXL

Manager - AI Engineering

On-siteposted 4mo ago

Skills required

About this role

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.

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 environments.

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 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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