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 rolesProficient in CI / CD tools : Jenkins, GitHub Actions, Azure DevOpsStrong expertise in Terraform, including managing and scaling infrastructure across large environmentsHands-on experience with Kubernetes in larger clusters , including workload distribution, autoscaling, and cluster monitoringStrong understanding of containerization technologies (Docker) and microservices architectureSolid grasp of cloud networking, security best practices, and observabilityScripting proficiency in Bash and PythonPreferred Skills :
Experience with MLflow, TFX, Kubeflow, or SageMaker PipelinesKnowledge of model performance monitoring and ML system reliabilityFamiliarity with AWS MLOps stack or equivalent tools on Azure / GCP#J-18808-Ljbffr