Azure DevOps Engineer Lead

NorthBay Solutions; Dubai; Hybrid; AED 120,000 - 200,000; Full time

Job summary

A leading AWS Premier Partner is seeking a highly skilled Lead DevOps Engineer to join their cloud and AI engineering team in Dubai. The ideal candidate will have 8 to 12 years of experience in DevOps and a strong foundation in cloud practices. Responsibilities include designing CI/CD pipelines, managing Infrastructure-as-Code with Terraform, and collaborating on ML model deployments. Candidates should have expertise in Kubernetes and cloud security practices, as well as scripting proficiency in Bash and Python. Flexibility to relocate to Abu Dhabi is required.

Qualifications

• 8 to 12 years of experience in DevOps and/or MLOps roles.
• Strong expertise in Terraform for infrastructure management.
• Hands-on experience with Kubernetes in larger clusters.

Responsibilities

• Design, implement, and manage CI/CD pipelines.
• Develop and maintain Infrastructure-as-Code using Terraform.
• Collaborate with data science teams for ML model deployment.

Skills

CI/CD tools proficiency

Terraform expertise

Kubernetes experience

Cloud networking and security

Scripting in Bash and Python

Tools

Jenkins

GitHub Actions

Azure DevOps

MLflow

Job description

Note: This role requires flexibility to relocate to Abu Dhabi (UAE) for onsite client requirements.

About the Role:

NorthBay, a leading AWS Premier Partner, is seeking a highly skilled Lead DevOps Engineer (Azure, Terraform) to join its growing cloud and AI engineering team. This role is ideal for candidates with a strong foundation in cloud DevOps practices and a passion for implementing scalable MLOps solutions.

Key Responsibilities:

• Design, implement, and manage CI/CD pipelines using tools such as Jenkins, GitHub Actions, or Azure DevOps
• Develop and maintain Infrastructure-as-Code using Terraform
• Manage and scale container orchestration environments using Kubernetes, including experience with larger production-grade clusters
• Ensure cloud infrastructure is optimized, secure, and monitored effectively
• Collaborate with data science teams to support ML model deployment and operationalization
• Implement MLOps best practices, including model versioning, deployment strategies (e.g., blue-green), monitoring (data drift, concept drift), and experiment tracking (e.g., MLflow)
• Build and maintain automated ML pipelines to streamline model lifecycle management

Required Skills:

• 8 to 12 years of experience in DevOps and/or MLOps roles
• Proficient in CI/CD tools: Jenkins, GitHub Actions, Azure DevOps
• Strong expertise in Terraform, including managing and scaling infrastructure across large environments
• Hands-on experience with Kubernetes in larger clusters, including workload distribution, autoscaling, and cluster monitoring
• Strong understanding of containerization technologies (Docker) and microservices architecture
• Solid grasp of cloud networking, security best practices, and observability
• Scripting proficiency in Bash and Python

Preferred Skills:

• Experience with MLflow, TFX, Kubeflow, or SageMaker Pipelines
• Knowledge of model performance monitoring and ML system reliability
• Familiarity with AWS MLOps stack or equivalent tools on Azure/GCP