Agent Runtime Platform Engineer (m/f/d)

Showcify, Inc.; Abu Dhabi; On-site; AED 180,000 - 240,000; Full time

Job summary

Showcify, Inc. seeks an Agent Runtime Platform Engineer to design and build the enterprise runtime foundation for AI agents and agentic applications.

This role emphasizes platform engineering with a focus on scalable, secure runtime capabilities across AKS, Azure Container Apps, Kubernetes, and cloud-native services. You will standardize patterns, manifests, and templates, enable self-service for engineering teams, ensure observability and production readiness, and collaborate with AI platform

Qualifications

• Experience designing cloud-native runtime patterns for agents.
• Hands-on with AKS, Kubernetes, and container platforms.
• Strong knowledge of security, observability, and scaling.
• Knowledge of security, observability, and cost control.
• Collaborates with AI platform teams and engineers.

Responsibilities

• Design and engineer runtime patterns for agent workloads across cloud-native platforms.
• Build reusable infrastructure patterns and platform APIs for consistent provisioning.
• Define standards for agent manifests and runtime configuration at scale.
• Standardize secure integration to models, MCP servers and enterprise APIs.
• Provide self-service templates, SDKs, and onboarding for teams.
• Ensure agent workloads are observable, scalable, and production-ready.

Skills

AKS

Azure Container Apps

Kubernetes

Containers

Networking

Workload identity

API gateways

Secrets management

Platform design

Security

GitHub Actions

Automation

AI agent architectures

Security & observability

Tools

Terraform

GitHub Actions

Deployment templates

Reusable platform modules

Environment-aware provisioning

Job description

Role Overview:

We are seeking an Agent Runtime Platform Engineer to design and build the enterprise runtime foundation for AI agents and agentic applications. This role is focused on platform engineering first, with a strong understanding of agent engineering standards and deployment patterns. The engineer will create secure, reusable, and self-service runtime capabilities that enable teams to deploy agents consistently across cloud-native environments such as AKS, Azure Container Apps, Kubernetes, APIs, event-driven services, and container platforms.

Key Responsibilities:

• Agent Runtime Platform: Design and engineer runtime patterns for agents, MCP servers, APIs, containerized services using AKS, Azure Container Apps, Kubernetes, queues, events, and cloud-native infrastructure.
• Platform Engineering Standards: Build reusable infrastructure patterns, and platform APIs that allow teams to provision and operate agent workloads consistently across environments.
• Agent Engineering Standards: Define standards for agent manifests, runtime configuration, tool definitions, so agent workloads can be managed at scale.
• Secure Integration Patterns: Standardize how agents connect to model, MCP servers and enterprise APIs using approved network, identity, and access-control patterns.
• Developer Self-Service: Provide paved-road templates, SDKs, reference implementations, documentation, and onboarding journeys that help application teams build and deploy agents without recreating runtime or infrastructure decisions.
• Operational Readiness: Ensure agent workloads are observable, scalable, and production-ready.

Technical & Professional Requirements:

• Strong hands-on experience with AKS, Azure Container Apps, Kubernetes, containers, networking, workload identity, ingress, API gateways, private connectivity, secrets management, and cloud-native runtime design.
• Expertise in Terraform, GitHub Actions or equivalent automation, reusable platform modules, deployment templates, and environment-aware provisioning practices.
• Working knowledge of AI agent architectures and API/service contracts.
• Ability to convert complex runtime and integration patterns into simple, reusable platform products for engineering teams.
• Strong understanding of security, observability, scaling, resilience, cost control, release promotion, and operational readiness for production workloads.
• Ability to work closely with AI platform engineers, AI Ops, cybersecurity, architecture, and application teams.