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

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