We are seeking a highly experienced Azure AI, AIOps & MLOps Architect to lead enterprise-scale AI platform engineering, cloud modernization, DevSecOps transformation, and intelligent automation initiatives.

The ideal candidate should possess deep expertise in Microsoft Azure, Azure AI Foundry, Azure OpenAI, Azure Machine Learning, Kubernetes, Terraform, Azure DevOps, and enterprise observability platforms. The role will focus on designing scalable AI platforms, implementing MLOps and AIOps capabilities, enabling Agentic AI architectures, and driving cloud-native engineering practices across the organization.

Key Responsibilities

Cloud Architecture & Engineering

•     Design and implement scalable, secure, and highly available solutions on Microsoft Azure.

•     Define cloud architecture standards, reference architectures, and best practices.

•     Lead cloud migration and modernisation initiatives across enterprise workloads.

•     Implement multi-region disaster recovery and business continuity strategies.

•     Oversee Azure networking, identity, security, and governance frameworks.

DevOps & CI/CD

•     Architect and implement end-to-end CI/CD pipelines using Azure DevOps or GitHub Actions.

•     Drive DevSecOps culture — embedding security scanning, quality gates, and compliance into the delivery pipeline.

•     Champion Infrastructure-as-Code (IaC) practices using Terraform, Bicep, or ARM templates.

•     Establish branching strategies, release management, and environment promotion standards.

•     Define and enforce platform engineering standards and internal developer tooling.

AI & Machine Learning Integration

•     Architect AI/ML solutions leveraging Azure AI services — Azure OpenAI, Azure Machine Learning, Azure AI Foundry, and Cognitive Services.

•     Design intelligent automation and agentic workflows integrated into enterprise DevOps processes.

•     Implement AI-powered capabilities such as code review assistance, anomaly detection, predictive analytics, and natural language automation.

•     Define AI governance frameworks: model evaluation, prompt management, responsible AI, and cost controls.

•     Design and implement enterprise MLOps frameworks.

•     Build automated model training, validation, deployment, and monitoring pipelines.

•     Establish model governance and lifecycle management.

Generative AI & Agentic AI

• Design enterprise GenAI solutions using Azure OpenAI.
• Build AI Agents using Azure AI Foundry.
• Develop Agent-to-Agent communication patterns.
• Implement Retrieval Augmented Generation (RAG) architectures.
• Build enterprise Knowledge Management and AI Skill Registry platforms.
• Design multi-agent orchestration frameworks.

Leadership & Stakeholder Engagement

•     Serve as the technical authority and subject matter expert for Azure AI and DevOps practices.

•     Mentor and guide junior architects, developers, and DevOps engineers.

•     Collaborate with business stakeholders, product owners, and vendors to translate requirements into technical solutions.

•     Produce architecture documentation, decision records (ADRs), and roadmaps.

•     Represent the technology function in enterprise architecture forums and governance boards.

Required Qualifications

•     Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.

•     12+ years of experience in cloud engineering and architecture.

•     5+ years of hands-on experience with Microsoft Azure across compute, networking, storage, identity, and data services.

•     Proven experience designing and implementing enterprise-grade CI/CD pipelines.

•     Strong hands-on expertise with Infrastructure-as-Code (Terraform, Bicep, or ARM).

•     Demonstrated experience architecting and deploying AI/ML solutions on Azure (Azure OpenAI, Azure ML, AI Foundry).

•     Deep knowledge of DevSecOps principles, tools, and practices.

•     Experience with containerisation and orchestration: Docker, Kubernetes (AKS).

•     Proficiency in scripting and development: Python, PowerShell, Bash.

•     Excellent communication and stakeholder management skills.

Preferred Qualifications

•     Microsoft Certified: Azure Solutions Architect Expert.

•     Microsoft Certified: DevOps Engineer Expert.

•     Microsoft Certified: Azure AI Engineer Associate.

•     Experience with Azure API Management (APIM), Event Grid, and Azure Functions.

•     Familiarity with Datadog, Prometheus, or equivalent observability platforms.

•     Experience in the real estate, retail, or enterprise industry sector.

•     Knowledge of agentic AI frameworks and LLM orchestration patterns (LangChain, Semantic Kernel, MCP).

•     Background in building Internal Developer Platforms (IDP).

Technical Skills

Domain

Technologies / Tools

Cloud Platform

Microsoft Azure (UAE North / Global)

DevOps & CI/CD

Azure DevOps, GitHub Actions, Jenkins

IaC

Terraform, Bicep, ARM Templates

AI / ML

Azure OpenAI, Azure AI Foundry, Azure ML, Cognitive Services

Containers

Docker, Kubernetes (AKS), Azure Container Apps

Identity & Security

Microsoft Entra ID, Azure Policy, Defender for Cloud

Observability

Datadog, Azure Monitor, Log Analytics, Application Insights

Databases

Azure SQL, PostgreSQL, Cosmos DB

Languages

Python, PowerShell, Bash, YAML