SRE DevOps Engineer

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