Gcp Cloud Engineer Id89421

Agileengine; Risaralda; Vor Ort; COP 397.390.000 - 596.086.000; Vollzeit

Benefits dieser Stelle

Professional growth

Competitive compensation

A selection of exciting projects

Flextime

Zusammenfassung

AgileEngine is seeking a skilled GCP Cloud Engineer to architect and manage cloud infrastructure using GKE, Cloud Run, and Terraform. You will lead a AWS-to-GCP migration workstream, assess source workloads, define target architectures, and drive production cutover.

Strong CI/CD with Azure DevOps and scripting in Python/Bash/PowerShell are required. Responsibilities include deploying and optimizing GCP resources, managing networking, IAM, and security, and ensuring cost efficiency across

Qualifikationen

• 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.
• Terraform expertise for provisioning cloud resources.
• Proficiency in Python, Bash, or PowerShell for automation.
• Knowledge of cloud security principles, IAM, and compliance standards.
• Hands-on involvement in at least one real AWS-to-GCP migration with explanation of what was migrated.
• Comfort delivering production-quality code with AI coding assistants.
• Upper-intermediate English level.

Aufgaben

• 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.
• Manage and configure Cloud Load Balancers 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 GKE.
• Work with Helm charts for microservices deployments.
• Automate scaling, rolling updates, and zero-downtime deployments.
• Move Kubernetes workloads across clouds (AWS EKS to GKE).
• Deploy and manage applications on Cloud Run and Cloud Functions with serverless workloads.

Kenntnisse

GCP

GKE

Terraform

Azure DevOps

Python

Bash

PowerShell

Cloud security & IAM

AWS-to-GCP migration

Tools

Docker

Helm

Go

Claude Code

Cursor

GitHub Copilot

Jobbeschreibung

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.

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.