Azure DevOps Engineer

Overview North Bay Solutions is seeking a highly skilled Lead Dev Ops Engineer (Azure, Terraform) to join its cloud and AI engineering team. This role is ideal for candidates with a strong foundation in cloud Dev Ops practices and a passion for implementing scalable MLOps solutions. Note: The role requires relocation or flexibility to travel to Abu Dhabi (UAE) for periodic onsite client engagements (2 to 3 months).Job details Job Title: Lead Dev Ops Engineer (Azure, Terraform)Employment Type: Full-time Key Responsibilities Design, implement, and manage CI/CD pipelines using tools such as Jenkins, Git Hub Actions, or Azure Dev Ops 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 (for example blue-green), monitoring data drift and concept drift, and experiment tracking with MLflow Build and maintain automated ML pipelines to streamline model lifecycle management Required Skills8 to 12 years of experience in Dev Ops and or MLOps roles Proficient in CI/CD tools: Jenkins, Git Hub Actions, Azure Dev Ops 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 Sage Maker Pipelines Knowledge of model performance monitoring and ML system reliability Familiarity with AWS MLOps stack or equivalent tools on Azure/GCP#J-18808-Ljbffr