Job Description

Job Title:

Lead DevOps Engineer (Azure, Terraform)

Employment Type:

Full-time

Note:

This role requires relocation or flexibility to travel to Abu Dhabi (UAE) for periodic onsite client engagements (2 to 3 months)

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



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