DevOps Support Engineer

Role Title: DevOps Support Engineer

Location: India Remote

About MediaRadar

MediaRadar, equips marketing, sales and analytics leaders with the intelligence they need to stay ahead. Our platform delivers always-on, AI-enabled Creative, Competitive, Commercial and Market Intelligence—spanning ad strategy, media spend, creative assets and brand messaging across 30+ media channels and five million brands.

With deep insights into more than 35 million ad and campaign assets and $280 billion in media spend, MediaRadar provides a single, interoperable source of truth that plugs seamlessly into enterprise analytics and AI systems. The result: faster, cleaner and more actionable intelligence that drives competitive advantage.

We are looking for a DevOps Support Engineer who can manage high-volume service requests and IT tickets, serve as the first line of support for infrastructure-related tasks, and use AI tools and prompt engineering to accelerate ticket resolution while maintaining internal SLAs.

What You'll Do

Ticket & Access Management

Execute standard access requests across Azure Entra ID, AWS IAM, and GitHub

Manage repository access and maintain centralized Entra groups for project-based resource assignments

Triage and resolve incoming “INTS” infrastructure and support tickets within defined SLAs (typically 5–10 business days)

Cloud Resource Operations

Provision and manage cloud resources including storage accounts (S3, Blob), Key Vaults, and Virtual Machines using standardized Terraform templates

Perform OS-level maintenance such as storage cleanup, file permissioning, and basic server troubleshooting

Support cost-optimization efforts by ensuring proper resource tagging and right-sizing cloud instances

Kubernetes Support

Manage namespace-level access and resource allocations within Kubernetes

Support developers with basic Kubernetes actions, including pod investigation and deployment verification via Argo CD

Facilitate the onboarding of new projects into the Kubernetes ecosystem

AI-Driven Workflow Optimization

Utilize AI coding agents (e.g., Claude) to generate scripts, validate Terraform plans, and troubleshoot infrastructure issues

Apply prompt engineering techniques to interact with Model Context Protocol (MCP) servers for automated policy checks and compliance verification

Contribute to the “Shared Services” knowledge base by documenting recurring solutions to enable developer self-service

Requirements

What You've Done

Built foundational knowledge of AWS or Azure, including compute, storage, and networking

Developed an understanding of Kubernetes fundamentals, including namespaces, pods, and deployments

Gained proficiency using LLMs and applying prompt engineering techniques

Demonstrated the ability to triage technical issues and follow standard operating playbooks

Spent 0–2 years in a technical support, IT, or junior cloud role

Originally posted on Himalayas