GCP Infrastructure DevOps Engineer

Absolutelabs

India

On-site

INR 2,800,000 - 3,800,000

Full time

14 days+

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Job summary

Absolutelabs is seeking a seasoned GCP Infrastructure DevOps Engineer to scale cloud platforms across Google Cloud with exposure to Azure and AWS. You will own landing zones, CI/CD pipelines, GKE workloads, and multi‑cloud connectivity while enforcing security and governance.

You will collaborate across architecture and security teams, optimize cloud spend, and enable AI/ML workloads with secure networking and private endpoints for Vertex AI pipelines.

Qualifications

  • 6+ years of hands-on infrastructure/DevOps experience with strong GCP depth.
  • Working knowledge of Azure and/or AWS is a plus.
  • Proven experience with Terraform, GitHub Actions, Cloud Build, and GitOps workflows.
  • Hands-on with GKE, Cloud Run, Compute Engine, and cloud networking.

Responsibilities

  • Design, build, and maintain GCP infrastructure using Terraform, landing zones, Shared VPC, IAM hierarchy, and Org Policy.
  • Own CI/CD pipelines with GitHub Actions and Cloud Build for automated deployments.
  • Manage GKE clusters, containerized workloads, networking, scaling, and security configs.
  • Implement hybrid and multi-cloud connectivity (Interconnect, VPN, DNS, Load Balancers).
  • Drive FinOps: budget alerts, committed use discounts, rightsizing, usage monitoring.
  • Enforce security controls including IAM least-privilege and VPC Service Controls.
  • Support AI/ML infra requirements with private endpoints for Vertex AI pipelines.
  • Collaborate with architecture, security, and platform teams to meet governance standards.
  • Troubleshoot infra issues across compute, networking, and pipelines in production.

Skills

GCP
Terraform
GitHub Actions
Cloud Build
GitOps
GKE
Cloud Run
Compute Engine
Networking
IAM Security
FinOps
Azure AWS

Tools

Terraform
GitHub Actions
Cloud Build
Ansible

Job description

Role Summary

We are looking for a GCP Infrastructure DevOps Engineer to own and scale our cloud infrastructure across Google Cloud Platform, with working exposure to Azure and AWS. This role sits at the intersection of infrastructure automation, cloud governance, and platform reliability, building secure landing zones, maintaining CI/CD pipelines, and keeping multi-cloud environments cost-optimized and compliant.


Key Responsibilities
  • Design, build, and maintain GCP infrastructure using Terraform, covering landing zones, Shared VPC, IAM hierarchy, and Org Policy constraints
  • Own CI/CD pipelines using GitHub Actions and Cloud Build, ensuring consistent, automated deployments across environments
  • Manage GKE clusters and containerized workloads, including networking, scaling, and security configurations
  • Implement and maintain hybrid and multi-cloud connectivity (Cloud Interconnect, ExpressRoute, VPN, Cloud DNS, Load Balancers)
  • Drive FinOps practices including budget alerting, committed use discounts, rightsizing, and usage monitoring to optimize cloud spend
  • Establish and enforce security controls such as IAM least-privilege, VPC Service Controls, DLP, and audit logging
  • Support infrastructure requirements for AI/ML workloads, including network isolation and private endpoints for Vertex AI pipelines
  • Automate infrastructure provisioning and configuration management using Terraform and AnsibleCollaborate with architecture, security, and platform teams to align infrastructure delivery with governance standards
  • Troubleshoot infrastructure issues across compute, networking, and deployment pipelines, supporting production environments.
Experience
  • 6+ years of hands-on infrastructure/DevOps experience, with strong depth in GCP; working knowledge of Azure and/or AWS is a plus
  • Proven experience with Terraform, GitHub Actions, Cloud Build, and GitOps workflows
  • Hands-on experience managing GKE, Cloud Run, and Compute Engine environments
  • Strong understanding of cloud networking (VPC, Interconnect, VPN, DNS, Load Balancers) and IAM/security fundamentalsExperience with FinOps practices and cost optimization at scale

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