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Lead DevOps Engineer (Azure, Terraform)

Roles & Responsibilities

  • 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

Requirements:

  • Design, implement, and manage CI/CD pipelines using Jenkins, GitHub Actions, or Azure DevOps
  • Develop and maintain Terraform Infrastructure-as-Code to provision and scale large cloud environments
  • Manage and scale Kubernetes clusters, including workload distribution, autoscaling, and cluster monitoring
  • Collaborate with data science teams to deploy ML models and implement MLOps practices, including model versioning, blue-green deployment strategies, data/concept drift monitoring, and MLflow-based experiment tracking, and build automated ML pipelines for model lifecycle management

Job description

Job Title: Lead DevOps Engineer (Azure, Terraform)
Employment Type: Full-time Remote (India) 

About the Role: 

NorthBay, a leading AWS Premier Partner, is seeking a highly skilled Lead DevOps (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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