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DevOps Support Engineer

MediaRadar · India

🌐 Remote📅 22/08/2026
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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
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