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)

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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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