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Lead Azure Terraform & AKS Specialist

IPEOPLE BUSINESS SOLUTIONS
12 - 15 Years
Chennai

Posted on: 26/06/2026

Job Description

Job Overview :

Experience Required : 12+ Years (Extensive Production Infrastructure)

Job Location : Chennai

Open Positions : 1 (High Priority / Immediate Panel Interviews)

Compensation / Rate : Best In the Industry

Mandatory Domain : Azure Kubernetes Services Operations

The Target Profile :

We are looking for a heavy-hitting Azure Platform Architect/Lead who can confidently write complex Azure Terraform modules completely from scratch. A successful candidate will have a proven track record of migrating legacy, manually configured environments over to clean, immutable Infrastructure as Code (IaC).

Mandatory Technical Depth :

1. Advanced Azure Kubernetes Service (AKS) :

- Hands-on management of complex, enterprise-scale production clusters.

- Deep mastery over Azure CNI networking, HPA/VPA scaling matrices, Node Pool lifecycles, and Ingress Controllers (Nginx / AGIC).

- The Test : You must be able to expertly diagnose and explain how you resolve a "Pod Pending" or "ImagePullBackOff" state within a heavily locked-down enterprise corporate network.

2. Advanced IaC (Terraform) :

- Complete mastery of Terraform state management, state recovery, and lock resolutions.

- Proven experience importing legacy manual cloud resources into code and creating highly reusable enterprise-wide modules.

3. GitOps Automation (Flux CD & Helm) :

- Hands-on implementation of Flux CD for automated reconciliation loops.

- Note : Standard "Push" pipelines (Jenkins / Azure DevOps) are treated as secondary; we require automated GitOps pull synchronization.

- Must be capable of authoring and troubleshooting native Helm charts from the ground up rather than simply executing basic commands.

4. Enterprise Observability (Dynatrace) :

- Production experience setting up Dynatrace instrumentation.

- Must be proficient in building Service Level Objectives (SLOs), segregating Management Zones, and leveraging Davis AI for root cause analysis.

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