شرح موقعیت
🤖 Agent Runtime Engineer - Focus: Azure | Kubernetes | Platform Engineering | AI Agents ⏳ 12-month initial contract 📍 Abu Dhabi We are looking for an experienced Agent Runtime Platform Engineer to help build the enterprise infrastructure that will power the next generation of AI agents and agentic applications. This is not a traditional AI/ML or prompt-engineering role. We are looking for someone with a strong Cloud and Platform Engineering background who understands how modern AI and agent workloads need to be deployed, secured, scaled and operated in production. You will build the reusable runtime foundations that allow engineering teams to deploy AI agents consistently across Azure, AKS, Kubernetes and containerised environments, creating the standards, automation and self-service capabilities needed to take agentic AI from experimentation into enterprise production. What You'll Be Doing Design and build enterprise runtime patterns for AI agents, MCP servers, APIs and containerised services. Build cloud-native platforms using AKS, Azure Container Apps, Kubernetes, containers, queues and event-driven architecture. Develop reusable infrastructure and deployment patterns that allow teams to provision agent workloads consistently across environments. Create self-service platform capabilities, including templates, SDKs, reference implementations and paved-road deployment patterns. Establish standards for agent manifests, runtime configuration and tool definitions. Define secure patterns for connecting agents to LLMs/models, MCP servers and enterprise APIs. Build reusable infrastructure using Terraform and Infrastructure as Code. Automate deployments and release processes through GitHub Actions or equivalent CI/CD tooling. Standardise networking, workload identity, secrets management, private connectivity, ingress and API gateway patterns. Ensure AI workloads are observable, resilient, scalable, secure and production-ready. Work closely with AI engineers, AI Ops, cybersecurity, architecture and application engineering teams. You will ideally come from a Platform Engineering, Azure Cloud, DevOps, SRE or AI Infrastructure background with strong hands-on engineering experience. You should have: Strong experience with Microsoft Azure and AKS (Azure Kubernetes Service). Excellent knowledge of Kubernetes, containers and cloud-native architecture. Experience with Azure Container Apps and containerised workloads. Strong hands-on Terraform / Infrastructure as Code experience. CI/CD experience with GitHub Actions, Azure DevOps or equivalent. Strong understanding of Azure networking, ingress, private connectivity and API gateways. Experience with workload identity, RBAC, secrets management and enterprise security patterns. Knowledge of observability, monitoring, resilience, scaling and production operations. Experience creating reusable platform modules, templates and self-service developer platforms. Working knowledge of Generative AI, LLMs, AI agents and agentic architectures. Understanding of APIs, service contracts and event-driven architectures. Experience with MCP (Model Context Protocol), MCP servers, AI agent runtimes or enterprise GenAI platforms would be particularly valuable. Why This Role? This is an opportunity to work beyond individual AI use cases and help define how AI agents operate at enterprise scale.