GCP DevOps

LTM; Hyderabad; Hybrid; INR 1,200,000 - 2,000,000; Full time

Job summary

LTM in Hyderabad is seeking a DevOps standout to manage Kubernetes Scheduler and Workflow artifacts, troubleshoot deployments, and recover failed schedulers and workflows. You will optimize configurations for performance and cost, and support deployments through stabilization and runbooks.

You will collaborate with Infrastructure teams on cloud platform issues, participate in capacity planning, and ensure 24x7 readiness for business-critical apps.

Qualifications

• Experience managing Kubernetes-based deployments and workflows on GCP.
• Proficient in troubleshooting deployments, pods, and services.
• Familiarity with cost optimization and performance tuning in cloud environments.

Responsibilities

• Manage application artifacts on Kubernetes Scheduler and Workflow services.
• Troubleshoot pod deployment and service failures.
• Recover failed schedulers and workflows.
• Optimize application configurations for performance and cost.
• Support deployments and postdeployment stabilization.
• Collaborate with Infrastructure teams for cloud platform issues.
• Maintain operational runbooks and cloud support procedures.
• Perform cloud capacity planning and environment health reviews.
• Support 24x7 operational readiness for businesscritical applications.

Skills

GCP Cloud Build

GKE

Kubernetes Admin

Cloud Logging

Cloud Monitoring

Cloud Scheduler

Cloud Workflows

Helm deployments

Secrets management

ConfigMap management

CI/CD support

Scripting - Bash

Python scripting

Incident management

RCA

Deployment troubleshooting

Runtime optimization

Capacity tuning

AMS Operations

Release support

Operational reporting

Production support

Tools

Terraform awareness

Apigee

Redis

AlloyDB

Dataflow

PubSub

DevSecOps practices

FinOps cloud cost optimization

AI platform deployment exposure

Job description

Key Responsibilities

• Manage applicationspecific artifacts on Kubernetes Scheduler and Workflow services


• Troubleshoot pod deployment and service failures


• Recover failed schedulers and workflows


• Optimize application configurations for performance and cost


• Support deployments and postdeployment stabilization


• Collaborate with Infrastructure teams for cloud platform issues


• Maintain operational runbooks and cloud support procedures


• Perform cloud capacity planning and environment health reviews


• Support 24x7 operational readiness for businesscritical applications

Mandatory Skills

• GCP Cloud Build, GCP Cloud Logging, GCP Cloud Monitoring, GKE, GCP Platform Services, Cloud Scheduler


• Cloud Workflows, Google Cloud Operations Suite


• Cloud Logging, Cloud Monitoring


• Kubernetes Administration, Deployment management


• Pod troubleshooting, Service troubleshooting


• ConfigMap and Secret management,Helm deployments, YAML configuration management, Autoscaling concepts, Configuration Automation, YAMLJSON configuration, CICD deployment support


• Application deployment troubleshooting, Runtime optimization, Capacity tuning, AMS Operations


• Incident management, Problem management, RCA


• Release support, Operational reporting, Production support


• Scripting - Bash, Shell, Python preferred

Good to Have Skills

• Terraform awareness, Apigee, Redis, AlloyDB, Dataflow, PubSub, DevSecOps practices, FinOps Cloud Cost Optimization, AI platform deployment exposure