GCP Cloud Engineer ID89421

Job Description

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE

We are looking for a GCP Cloud Engineer to architect and manage cloud infrastructure using GKE, Cloud Run, and Terraform. This person leads a dedicated AWS-to-GCP migration workstream, assessing source workloads, defining target architectures, and driving production cutover. Strong CI/CD experience with Azure DevOps and scripting in Python, Bash, or PowerShell rounds out the role.

WHAT YOU WILL DO

Cloud Infrastructure

- 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.

Kubernetes & Serverless

- 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.

CI/CD & DevOps

- 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.

AWS-to-GCP Migration

- 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.

MUST HAVES

- 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.

NICE TO HAVES

- Experience with GCP target data platforms such as Databricks or BigQuery.

- Experience migrating network and infrastructure components, not only application workloads.

- Strong Go and/or Python engineering depth.

- Experience leading large-scale cloud migration programs.

- Experience with MCP, reusable AI Skills, or agentic AI workflows.

- Cross-cloud cost and performance optimization experience.

PERKS AND 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.

Meet Our Recruitment Process

Application → Coding Challenge → Video Interview → Technical Interview or Hiring Manager Interview

Each step helps us understand your skills and overall fit.

If it’s a match, you’ll receive an offer.

Requirements
Required Skills & Qualifications Experience: 4+ years in Cloud Engineering, with a focus on GCP. Cloud Expertise: Strong knowledge of GCP services (GKE, Compute Engine, IAM, VPC, Cloud Storage, Cloud SQL, Cloud Functions, Cloud Run, Cloud Load Balancing). Kubernetes & Containers: Experience with GKE, Docker, GKE networking, and Helm. DevOps Tools: Hands-on experience with Azure DevOps for CI/CD pipeline automation. Infrastructure-as-Code (IaC): Expertise in Terraform for provisioning cloud resources. Scripting & Automation: Proficiency in Python, Bash, or PowerShell for automation. Security & Compliance: Knowledge of cloud security principles, IAM, and compliance standards. Migration Track Record: 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. AI-Assisted Engineering: Comfortable delivering production-quality code with Claude Code, Cursor, GitHub Copilot, Codex, or comparable AI coding assistants.