AI Platform Engineer

Tanqeeb; Dubai; On-site; AED 300,000 - 540,000; Full time

Job summary

Cloud AI Services in the United Arab Emirates seeks a senior cloud AI professional with hands-on experience across Azure AI Services (Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Speech, Document Intelligence) and AWS Bedrock. You will drive production deployments, manage AKS and container lifecycles, and implement API management, observability, and robust DevOps automation.

Analytical tasks include cost and performance tuning, prompt engineering, and governance with responsible-AI

Qualifications

• Hands-on production experience with Microsoft Azure AI Services including Azure OpenAI, Azure AI Foundry-related services, Azure AI Search, Azure Speech, Document Intelligence, and Content Safety and equivalent fluency with AWS AI Services, including AWS Bedrock and supporting model and content services.
• Familiarity with Core42 Compass for in-region inference is required.
• Strong working knowledge of Microsoft Agent Framework and LangGraph, including agent orchestration, tool calling, skill composition, memory and state management, planning patterns, multi-agent execution topologies, and human-in-the-loop checkpoints.
• Practical expertise in prompt-level troubleshooting, token consumption analysis, context-window management, model configuration tuning, endpoint health monitoring, and throttling and latency analysis.
• Deep operational experience with Azure Kubernetes Service, including Kubernetes core constructs, Helm release management, autoscaling behaviour, container troubleshooting, and Docker image lifecycle.
• Strong expertise in Azure API Management, including policy, values, products, subscriptions, OAuth 2.0, JWT validation, and backend routing.
• Expertise in Comet Opik for distributed agent tracing, and Azure Monitor, Application Insights, Log Analytics, and AWS CloudWatch integration.
• Comfort with Git-based workflows, CI/CD pipelines (GitLab CI/CD or Azure DevOps), infrastructure as code (Terraform or Bicep), and scripting in Python, PowerShell, Bash.
• Working experience with ElevenLabs APIs and SDKs, voice-agent integrations, and real-time processing.
• Hands-on with Microsoft Entra ID, RBAC, Azure Key Vault, private networking, and AI governance frameworks.

Responsibilities

• Lead deployment of Azure AI and AWS AI services in production environments.
• Manage Kubernetes-based deployments, container lifecycles, and platform networking.
• Oversee DevOps automation, CI/CD pipelines, and IaC practices for scalable services.
• Ensure security, governance, data protection, and responsible-AI policy enforcement across platforms.

Skills

Azure AI Services

Azure OpenAI

AWS Bedrock

Kubernetes

Containers

DevOps

Python scripting

Security governance

Observability

REST APIs

Education

Tools

Azure Kubernetes Service

Docker

Terraform

Bicep

kubectl

GitLab CI/CD

Azure DevOps

Job description

Cloud AI Services

Hands-on production experience with Microsoft Azure AI Services including Azure OpenAI, Azure AI Foundry-related services, Azure AI Search, Azure Speech, Document Intelligence, and Content Safety and equivalent fluency with AWS AI Services, including AWS Bedrock and supporting model and content services. Familiarity with Core42 Compass for in-region inference is required.

Agentic AI Frameworks

Strong working knowledge of Microsoft Agent Framework and LangGraph, including agent orchestration, tool calling, skill composition, memory and state management, planning patterns, multi-agent execution topologies, and human-in-the-loop checkpoints. Ability to read and reason about agent graphs, conditional edges, retry policies, and tool schemas to diagnose execution-level issues quickly.

LLM Operations

Practical expertise in prompt-level troubleshooting, token consumption analysis, context-window management, model configuration tuning, endpoint health monitoring, Azure OpenAI PTU capacity and quota management, throttling and latency analysis, fallback handling, and responsible-AI controls including content filtering and safety policies.

Kubernetes and Containers

Deep operational experience with Azure Kubernetes Service, including Kubernetes core constructs (deployments, pods, services, ingress, namespaces, ConfigMaps, secrets), Helm-based release management, autoscaling behaviour, container troubleshooting, and Docker image lifecycle. Comfort with kubectl, kustomize, and platform-level network and identity constructs.

API and MCP Gateway

Strong expertise in Azure API Management, including API policies, named values, products, subscriptions, OAuth 2.0 and OpenID Connect flows, managed identities, JWT validation, rate limiting, caching, and backend routing. Working knowledge of REST APIs and event-driven integration patterns. Specific experience with the Model Context Protocol (MCP) including MCP servers, MCP clients, tool definitions, and gateway-mediated MCP patterns is highly desirable.

Observability

Expertise in Comet Opik for distributed agent and prompt tracing, including trace inspection, evaluation runs, drift detection, and dashboard construction. Strong working knowledge of Azure Monitor, Application Insights, Log Analytics, and AWS CloudWatch, with the ability to construct correlated views across logs, metrics, traces, and business indicators using correlation identifiers.

DevOps and Automation

Comfort with Git-based workflows, CI/CD pipelines (GitLab CI/CD or Azure DevOps), infrastructure as code (Terraform or Bicep), release automation, and deployment validation. Strong scripting in Python, PowerShell, and Bash for operational tooling, log mining, and remediation automation.

Voice AI

Working experience with ElevenLabs APIs and SDKs, voice-agent integrations, real-time audio processing, session-level troubleshooting, latency and audio-quality analysis, and integration with conversational AI and telephony layers.

Security and Governance

Hands-on experience with Microsoft Entra ID, RBAC, managed identities, Azure Key Vault, secrets and certificate management, private networking and Private Link, vulnerability management, audit logging, data protection controls, and AI governance frameworks including model access management and responsible-AI policy enforcement.

Service Management

Practical application of ITIL practices including incident management, problem management, change management, service requests, SLA and OLA management, root-cause analysis, and major incident management within an enterprise service-management toolset such as ServiceNow.

Desired Candidate Profile

The following certifications are considered desirable:

• Microsoft Azure Administrator or Azure Solutions Architect Expert
• Microsoft Azure AI Engineer Associate
• AWS Solutions Architect or AWS Certified Machine Learning Specialty
• Certified Kubernetes Administrator (CKA) or Certified Kubernetes Application Developer (CKAD)
• ITIL Foundation or higher
• DevOps, Site Reliability Engineering, Cybersecurity, or AI Governance certifications from a recognized body