A
AgileEngine
Devops
GCP Cloud Engineer ID89421
GCPGoogle Kubernetes EngineCloud RunTerraformAzure DevOpsPythonBashPowerShellGoogle Cloud StorageGoogle Cloud SQLFilestoreCloud Load BalancersHelmGoogle Cloud FunctionsDockerGoCompute EngineIAMVPCAnthropicCursorGitHub CopilotCodexDatabricksBigQuery
Responsibilities
- Architect, deploy, and maintain GCP cloud resources via Terraform or other automation.
- Implement Google Cloud Storage, Cloud SQL, and Filestore for data storage and processing needs.
- Manage and configure Cloud Load Balancers (HTTP(S), TCP/UDP, and SSL Proxy) for high availability and scalability.
- Design and implement cloud networking, IAM, security, and landing-zone components.
- Optimize resource allocation, monitoring, and cost efficiency across GCP environments.
- Deploy, manage, and optimize workloads on Google Kubernetes Engine (GKE).
- Work with Helm charts for microservices deployments.
- Automate scaling, rolling updates, and zero-downtime deployments.
- Move Kubernetes workloads across clouds where required, including AWS EKS to GKE.
- Deploy and manage applications on Cloud Run and Cloud Functions for scalable, serverless workloads.
- Optimize containerized applications running on Cloud Run for cost efficiency and performance.
- Design, implement, and manage CI/CD pipelines using Azure DevOps.
- Automate infrastructure deployment using Terraform, Bash, and PowerShell scripting.
- Integrate security and compliance checks into the DevOps workflow (DevSecOps).
- Migrate or redesign existing pipelines as workloads move from AWS to GCP.
- Assess existing AWS infrastructure and workloads and define appropriate GCP target architectures.
- Plan and execute production AWS-to-GCP migration activities, including workload cutover and rollback planning.
- Plan and execute cross-cloud data migration covering object storage, warehouses, and managed services.
- Support reliability, performance, scalability, and cost optimization during and after migration.
- Automate migration and operational activities using Python, Bash, PowerShell, Go, or platform tooling.
- Use AI coding assistants as a core part of daily engineering work — migration analysis, implementation, troubleshooting, and documentation.
Requirements
- 4+ years in Cloud Engineering, with a focus on GCP.
- Strong knowledge of GCP services (GKE, Compute Engine, IAM, VPC, Cloud Storage, Cloud SQL, Cloud Functions, Cloud Run, Cloud Load Balancing).
- Experience with GKE, Docker, GKE networking, and Helm.
- Hands-on experience with Azure DevOps for CI/CD pipeline automation.
- Expertise in Terraform for provisioning cloud resources.
- Proficiency in Python, Bash, or PowerShell for automation.
- Knowledge of cloud security principles, IAM, and compliance standards.
- Demonstrated hands-on involvement in at least one real AWS-to-GCP migration — not just multi-cloud familiarity — with the ability to explain what was migrated and what broke.
- Comfortable delivering production-quality code with Claude Code, Cursor, GitHub Copilot, Codex, or comparable AI coding assistants.
- Upper-intermediate English level.
Benefits
- Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps
- Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities
- A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands
- Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office — whatever makes you the happiest and most productive.
Who to contact
GCP Cloud Engineer ID89421
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