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