Gcp Cloud Engineer Id89421

Agileengine; Rosarito; Híbrido; MXN 700.000 - 1.200.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth

Competitive USD-based compensation

A selection of exciting projects

Flextime

Descripción de la vacante

AgileEngine is seeking a GCP Cloud Engineer to architect and manage cloud infrastructure using GKE, Cloud Run, and Terraform. This role leads an AWS-to-GCP migration workstream and collaborates on production cutovers, with strong CI/CD experience and scripting in Python, Bash, or PowerShell.

You'll design cloud networking, IAM, security, and landing zones, optimize costs, and ensure reliability across multiple GCP environments while leveraging AI coding assistants to accelerate development.

Formación

• 4+ years in Cloud Engineering with a focus on GCP.
• Strong knowledge of GCP services including 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 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 with ability to explain migrations.

Responsabilidades

• Architect, deploy, and maintain GCP resources using Terraform or other automation.
• Implement data storage via Google Cloud Storage, Cloud SQL, and Filestore.
• Manage Cloud Load Balancers for high availability and scalability.
• Design cloud networking, IAM, security, and landing-zone components.
• Optimize resource allocation, monitoring, and cost across GCP environments.
• Deploy and manage workloads on GKE and Cloud Run; use Helm charts for deployments.
• Design and manage CI/CD pipelines using Azure DevOps; automate infrastructure with Terraform, Bash, and PowerShell.
• Migrate workloads from AWS to GCP and ensure reliable cutover and rollback.

Conocimientos

Cloud engineering

GCP services knowledge

Kubernetes

CI/CD

Automation scripting

AI coding assistants

English (Upper-intermediate)

Herramientas

Terraform

Docker

Helm

Azure DevOps

Python

Bash

PowerShell

Descripción del empleo

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.