Gcp Cloud Engineer Id89421

Agileengine; Región Centro; Híbrido; MXN 1.636.000 - 2.364.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Professional growth

Competitive compensation

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. You will lead the AWS-to-GCP migration workstream, assess workloads, define target architectures, and drive production cutover.

Ideal candidates have 4+ years in cloud engineering with strong GCP expertise, Terraform, Azure DevOps, and scripting skills. This role offers hybrid work options in Mexico and USD-based compensation.

Formación

• 4+ years in cloud engineering with focus on GCP.
• Experience with GKE, Terraform, Helm, and Docker.
• Hands-on AWS-to-GCP migration projects required.

Responsabilidades

• Architect, deploy, and maintain GCP resources via Terraform.
• Lead AWS-to-GCP migration workstreams and cutover planning.
• Develop CI/CD pipelines using Azure DevOps and scripting.
• Optimize cost, security, and performance across cloud platforms.

Conocimientos

GCP

Terraform

Azure DevOps

Python/Bash/PowerShell

GKE

Docker

Security & IAM

AWS-to-GCP migration

AI coding assistants

English

Herramientas

Helm

Cloud Run

Cloud Functions

Go

Cloud Load Balancing

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.