Senior Cloud Engineer – Azure MLOps / AIOps

Job Title

Senior Cloud Engineer – MLOps / AIOps (Azure | Databricks | AKS/ARO)

Location

ITPL, Bangalore (Hybrid – 3 days/week)

Experience

7–10 Years

Employment Type

Full-time

About the Role

We are looking for a Senior Cloud Engineer with strong expertise in Azure cloud and MLOps/AIOps to drive enterprise-scale cloud transformation and ML platform engineering.

You will play a key role in Azure migration initiatives, building scalable ML pipelines, and enabling reliable, secure, and cost-optimized cloud platforms.

Key Responsibilities

• Lead and support Azure migration initiatives with a focus on MLOps/AIOps readiness
• Design, develop, and manage Databricks jobs, workspaces, and pipelines
• Deploy and manage applications on AKS or ARO (Kubernetes)
• Build and maintain CI/CD/CT pipelines using Azure DevOps or GitHub Actions
• Collaborate with cross-functional teams and participate in vendor discussions
• Implement Infrastructure as Code (IaC) for scalable deployments
• Enable observability through monitoring, logging, and alerting frameworks
• Support ML lifecycle operations including model tracking, packaging, and deployment
• Ensure cloud security, governance, and cost optimization best practices

Required Skills & Experience (Must-Have)

• 7–10 years of overall IT experience with a strong focus on Azure cloud
• 3+ years of experience in MLOps/AIOps and production ML systems
• Hands-on experience in Azure migration projects, including planning/strategy for MLOps/AIOps workloads, and participation in vendor discussions
• Strong hands-on expertise with Azure Databricks (jobs, workspaces, clusters)
• Proven experience deploying and managing workloads on AKS or ARO (Kubernetes)
• Solid experience building and managing CI/CD/CT pipelines using Azure DevOps or GitHub Actions
• Experience implementing observability solutions (monitoring, logging, alerting) in cloud environments
• Strong understanding and practical experience in cloud security, governance, and cost optimization
• Hands-on experience working in production environments (not just POCs or academic projects)
• Proficiency in collaborating with cross-functional teams and stakeholders

Good to Have

• Experience with MLflow (tracking & model registry)
• Hands-on exposure to Terraform / Infrastructure as Code
• Familiarity with GitOps tools (ArgoCD / Flux)
• Experience in model serving and packaging
• Exposure to enterprise cloud migration projects