Agent Runtime Platform Engineer – UAE

Location

United Arab Emirates

Job Category

• Information Technology (IT) & Software
• Engineering & Technical
• Telecommunications
• Remote / Work-from-Home Opportunities

Job Overview

We are seeking an experienced Agent Runtime Platform Engineer to support the design, development, and operation of cloud-native runtime platforms for AI-powered workloads in the UAE. The role is suited to professionals with strong hands-on expertise in Microsoft Azure, Kubernetes, containers, networking, infrastructure automation, and cloud-native runtime architecture.

The successful candidate will work across AKS, Azure Container Apps, workload identity, ingress, API gateways, private connectivity, secrets management, and other cloud-native technologies. The position will also involve building reusable infrastructure modules and deployment templates using Terraform and GitHub Actions or equivalent automation technologies.

This opportunity offers long-term career growth in cloud platform engineering, AI infrastructure, DevOps, and AI agent platform development. The engineer will collaborate with AI platform, AI Ops, cybersecurity, architecture, and application teams while developing expertise in secure, scalable, resilient, and production-ready runtime platforms.

Key Responsibilities

• Design and develop cloud-native runtime platforms for AI agent workloads.
• Build and manage Azure Kubernetes Service (AKS) environments.
• Work with Azure Container Apps and containerized workloads.
• Design and maintain Kubernetes-based runtime environments.
• Implement networking, ingress, API gateways, and private connectivity solutions.
• Configure and manage workload identity and secrets management.
• Develop reusable infrastructure modules using Terraform.
• Build deployment templates and environment-aware provisioning workflows.
• Implement CI/CD automation using GitHub Actions or equivalent tools.
• Develop reusable platform capabilities for engineering teams.
• Translate complex runtime and integration requirements into simple platform products.
• Support AI agent architectures and API/service contracts.
• Implement security, observability, scalability, resilience, and operational-readiness practices.
• Support production workloads and release promotion processes.
• Monitor and optimize infrastructure and platform costs.
• Collaborate with AI platform engineers, AI Ops, cybersecurity, architecture, and application development teams.
• Contribute to continuous improvement of platform engineering standards and operational practices.

Requirements & Qualifications

• Strong hands-on experience with AKS and Kubernetes.
• Experience with Azure Container Apps and containerized workloads.
• Strong understanding of cloud networking and cloud-native runtime design.
• Experience with workload identity and identity-based access controls.
• Experience with ingress and API gateway technologies.
• Knowledge of private connectivity and secure cloud networking.
• Experience with secrets management solutions.
• Strong expertise in Terraform.
• Experience with GitHub Actions or equivalent CI/CD automation technologies.
• Experience developing reusable platform modules and deployment templates.
• Knowledge of environment-aware infrastructure provisioning.
• Working knowledge of AI agent architectures.
• Understanding of API and service contracts.
• Strong understanding of security and production governance.
• Experience with observability and monitoring.
• Knowledge of scaling, resilience, and cost-control practices.
• Understanding of release promotion and production-readiness processes.
• Strong communication and collaboration skills.
• Ability to work effectively with cross-functional technology teams.

Salary, Benefits & Career Growth

Salary details have not been provided by the employer.

The role provides opportunities for career progression in cloud platform engineering, Kubernetes, Azure infrastructure, AI agent platforms, DevOps, and production engineering. Professionals can further strengthen their expertise through hands-on experience with cloud-native runtime architecture, infrastructure as code, AI workloads, platform security, observability, scalability, and operational readiness.

Training, certification, and skill-development opportunities may be available depending on project requirements and organizational programs.

Application Process

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