Senior AI Engineer - Agentic AI Azure Solutions

About the role

The company's Data & AI platform runs on Azure in a hub-spoke landing zone with private networking, hosting AI agents, web applications and data pipelines, some delivered by external partners. The Senior AI Engineer owns how the platform is provisioned, secured and deployed, moving manual releases to automated, approval-gated delivery. The role is initially remote, based in Abu Dhabi with potential onsite relocation.

Key responsibilities

• Build and maintain infrastructure as code in Terraform and Bicep: modules, remote state and policy.
• Manage the environment model (dev, UAT, production and ephemeral staging).
• Create reusable deployment blueprints for App Service, Functions, Logic Apps, AI services, databases and storage.
• Build multi-stage Azure DevOps YAML pipelines with templates, environments and approval gates.
• Enforce branch policies and PR review so no change reaches production unreviewed.
• Deploy and operate web applications and APIs on App Service, Functions and Container Apps.
• Own networking and access: private endpoints and DNS, RBAC least privilege, managed identities, Key Vault and scoped partner access.
• Set up monitoring, alerting and cost controls with Azure Monitor, Log Analytics and tagging.

Required profile

• 6+ years in DevOps / platform engineering, including 3+ years on Azure in production.
• Experience conducting Azure infrastructure, pipeline and access reviews.
• Experience building reusable deployment blueprints for applications and AI workloads.

Required skills

• Expert Azure DevOps: multi-stage YAML pipelines, templates, environments, service connections, branch policies and approval gates.
• Strong Terraform and Bicep, including reusable module design, state management and policy-as-code.
• Azure networking and security: hub-spoke, private endpoints, VNet integration, Entra ID, RBAC, KeyVault.
• Application deployment on App Service, Functions, Logic Apps Standard and containers.
• Scripting in PowerShell, Bash and Azure CLI.
• Mandatory: Azure Monitor, Log Analytics (KQL) and Application Insights, with operational runbooks.
• Preferred: deploying AI workloads (Azure AI Foundry, Azure OpenAI, AI Search) and Databricks automation; AZ-400 or AZ-305 certification.