Lead DevOps Engineer

aon

Bangalore 10 Years Exp Posted 59d ago

Job Description

  1. DevOps Strategy, Architecture & Delivery (Hands-On)
  • Own DevOps strategy across multiple applications
  • Build and maintain CI/CD pipelines (Azure DevOps)
  • Implement and run low-downtime deployments (blue/green, canary)
  • Develop and manage Terraform-based IaC
  • Architect and operate Azure infrastructure
  • Implement monitoring, logging, and observability
  • Embed security and compliance into pipelines
  • Deliver DevOps outcomes end-to-end
  1. Leadership, Coordination & Execution (Player-Coach)
  • Mentor and guide the DevOps engineer
  • Act as hands-on lead (“player-coach”)
  • Prioritize and manage work across applications
  • Coordinate with dev, QA, product, and business teams
  1. Operations, Support & Continuous Improvement
  • Lead incident response and root cause analysis
  • Ensure system reliability and performance
  • Continuously improve pipelines, tooling, and practices
  • Use AI to enhance delivery with proper governance

 

Core technical profile

  • CI/CD & Azure DevOps
    • Strong experience with Azure DevOps Pipelines
    • Able to design and operate blue/green deploymentsand other low‑downtime deployment strategies
  • Infrastructure as Code
    • Hands‑on experience with Terraformfor Azure
    • Able to define and maintain reusable IaC patterns and modules
  • Azure Services
    • Solid understanding of core Azure services(compute, storage, networking, monitoring, etc.)
    • Experience partnering with central Cloud/Azure teamsto get designs implemented and approved

Leadership / ownership

  • Comfortable taking the leadon DevOps for a complex application
  • Can design an overall DevOps solution(build, release, environments, monitoring, rollback)
  • Able to track work from initiation through completion, coordinating across developers, PM/BA, and cloud/platform teams

AI usage

  • Uses AI effectivelyto improve pipeline reliability, infrastructure quality, and documentation
    • Applies appropriate guardrails(e.g., validation of AI output, security and compliance awareness)

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