Lead Azure DevOps & MLOps Engineer (Terraform/K8s)

NorthBay Solutions LLC; Abu Dhabi; On-site; AED 600,000 - 900,000; Full time

Job summary

NorthBay Solutions LLC in Abu Dhabi seeks a Lead DevOps Engineer specialized in Azure Terraform to drive cloud infrastructure and ML pipeline operations. You will architect scalable CI/CD, IaC, and monitoring practices across large production environments.

Responsibilities include managing Terraform-based infrastructure, Kubernetes clusters, and collaboration with data science teams to deploy, version, and monitor ML models using MLOps best practices.

Qualifications

• 8–12 years of DevOps/MLOps experience.
• Proficiency with CI/CD tools: Jenkins, GitHub Actions, Azure DevOps.
• Expertise in Terraform and large-scale Kubernetes.
• Containerization with Docker and microservices.
• Scripting in Bash and Python.

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.

Skills

DevOps/MLOps

CI/CD tooling

Terraform

Kubernetes

Docker

Security & Observability

Bash

Python

Tools

Jenkins

GitHub Actions

Azure DevOps

Job description

NorthBay Solutions LLC in Abu Dhabi seeks a Lead DevOps Engineer specialized in Azure Terraform to drive cloud infrastructure and ML pipeline operations. You will architect scalable CI/CD, IaC, and monitoring practices across large production environments.

Responsibilities include managing Terraform-based infrastructure, Kubernetes clusters, and collaboration with data science teams to deploy, version, and monitor ML models using MLOps best practices.