Senior Cloud DevOps Engineer - Azure & AI Solutions
Location:
Abu Dhabi
Role Overview
We are seeking a highly skilled Senior Cloud DevOps Engineer with strong expertise in Azure and AI platforms to design, deploy, and manage scalable cloud and MLOps solutions. This role will drive automation, governance, security, and end-to-end AI infrastructure delivery.
Key Responsibilities
Architect and deploy scalable AI and cloud platforms using Azure VMs, AKS, and Azure Functions
Administer Azure Subscriptions and Resource Groups with strong governance using Azure Policy, Blueprints, and RBAC
Automate infrastructure using Terraform through reusable modules, secure state management, and CI/CD integration
Implement secure networking using Azure Firewall, VNets, NSGs, and Private Endpoints
Monitor and optimize cloud resources using Azure Advisor, Cost Management, and AWS CloudWatch for hybrid setups
Deploy and manage ML models using Azure Machine Learning, MLflow, and Azure ML Endpoints
Build and operate robust MLOps pipelines using Azure DevOps, GitHub Actions, and Terraform
Containerize and deploy models using AKS, ACI, and optionally Amazon SageMaker
Track model performance and data drift using Azure Monitor, Application Insights, and Log Analytics
Integrate Azure Cognitive Services, Azure OpenAI, and optionally AWS Rekognition or Comprehend
Apply Generative AI engineering principles to build scalable and modular AI solutions
Collaborate closely with AI, Data Science, UI/UX, and engineering teams for end-to-end delivery
Create documentation standards and reusable templates for AI and infrastructure projects
Apply DevOps best practices using Docker, CI/CD pipelines, and Infrastructure as Code
Ensure compliance with enterprise policies, security standards, and service guidelines
Ideal Candidate Profile
5+ years of hands-on experience in Azure-based cloud and AI solution delivery
Strong expertise in Terraform, including module development, remote state management, and CI/CD integration
Proven experience in cloud infrastructure, MLOps, containerization, and DevOps automation
Bachelor's degree in Computer Science, AI, Software Engineering, Statistics, or related field (Master's preferred)
Azure certifications such as AZ-104, AZ-305, or DP-100 are a strong advantage
Exposure to both Azure and AWS environments
Strong skills in data preparation, feature engineering, and large-scale dataset handling
Ability to convert technical insights into clear business value
Experience working cross-functionally with engineering, product, and business teams
Interested candidates can share their resume at:
[email protected]
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