SRE DevOps Engineer

Job description

**Job Title:** SRE DevOps Engineer **Job Location:** Bengaluru , Hyderabad & Chennai **Key Responsibilities :** **Infrastructure Automation (Python-driven)** - Develop and maintain Python scripts/tools to automate - Provisioning (VMs, containers, cloud resources) - Configuration management - System health checks and maintenance tasks - Build reusable automation frameworks and APIs - Reduce manual ops work through end-to-end automation pipelines - Create internal tools (Python-based) for dev productivity **CI/CD Pipeline Engineering** - End-to-end ownership of CI/CD pipelines, deployments, and production releases - Automate , Build, test, deployment workflows - Integrate Python automation for: Test orchestration & Deployment validations **Site Reliability Engineering (SRE) Practices** - Define and manage:SLIs, SLOs, SLAs - Improve system reliability, scalability, and uptime - Perform: Root Cause Analysis (RCA) &Incident management & postmortems **Monitoring, Logging & Observability** - Implement monitoring solutions: Prometheus, Grafana, ELK, Datadog, Splunk - Use Python for: Custom metrics collection , Log parsing and analytics & Alert automation - Support of ML platform operations and Kubernetes ecosystem **Cloud & Infrastructure Management** - Manage cloud platforms (AWS / Azure / GCP): Compute, storage, networking, serverless - Implement Infrastructure as Code (IaC): - Terraform, CloudFormation, ARM templates **Experience & Mandatory skills:** Overall 5 to 8 yrs exp with strong hold on Python Automation - Cloud: Microsoft Azure , IaC: Terraform - CI/CD: GitHub, GitHub Actions, Octopus Deploy - Containers & Orchestration: Kubernetes, AKS - MLOps: Kubeflow, KServe, Istio, EvidenceAI - Monitoring: ELK Stack, Prometheus, Grafana - Web/Hosting: IIS (Windows Server) - Database: SQL Server - Scripting: Python, Bash, PowerShell - End-to-end ownership of CI/CD pipelines, deployments, and production releases - Ownership of monitoring, alerting, and platform reliability - Responsibility for cloud infrastructure lifecycle management - Active contribution to platform modernization and migration initiatives - Support of ML platform operations and Kubernetes ecosystem - Direct involvement in customer onboarding and production support