Devops Engineer — Cloud Infra, Ci/Cd & Automation

Esentia Recursos Humanos; Buenos Aires; Remote; ARS 137,078,000 - 182,771,000; Full time

Benefits offered by this job

Professional growth

USD-based compensation

Top-tier clients and projects

Flextime – remote and office options

Job summary

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

Strong CI/CD experience with Azure DevOps and scripting in Python, Bash, or PowerShell are key assets. The role emphasizes designing scalable cloud foundations, security, and cost optimization while delivering reliable, production-grade solutions

Qualifications

• 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).
• 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 explanations of what migrated and what broke.
• Upper-intermediate English.

Responsibilities

• Architect, deploy, and maintain GCP resources via Terraform or other automation.
• Implement Google Cloud Storage, Cloud SQL, and Filestore for data storage needs.
• 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 optimize workloads on GKE and Helm charts for microservices.
• Automate scaling, rolling updates, and zero-downtime deployments.
• Move Kubernetes workloads across clouds when required (AWS EKS to GKE).
• Deploy and manage applications on Cloud Run and Cloud Functions for serverless workloads.
• Optimize containerized apps on Cloud Run for cost efficiency.

Skills

GCP

GKE

Terraform

Azure DevOps

Python

Bash

PowerShell

Kubernetes

Docker

AWS-to-GCP migration

English

Tools

Terraform

Azure DevOps

Docker

Kubernetes

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

• 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.

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

6+ years of professional experience in Cloud Engineering, Platform Engineering, DevOps or Site Reliability Engineering. Deep hands‑on expertise with AWS production environments, including cloud architecture, security, networking fundamentals, access management, monitoring, capacity, and operational troubleshooting. Advanced experience with Kubernetes and Amazon EKS, including workload deployment, cluster and application troubleshooting, observability, scaling, upgrades, access, and reliability. Hands‑on experience operating Argo Workflows or a comparable orchestration platform supporting production data workloads. Strong experience with Infrastructure as Code, preferably Terraform, and with source‑controlled configuration, CI/CD, release automation, and rollback practices. Strong experience designing and operating observability, logging, monitoring, alerting, and incident‑routing solutions for distributed production platforms. Demonstrated ability to lead major incidents and cross‑functional troubleshooting across infrastructure, applications, data pipelines, and analytics layers. Experience operating production platforms with defined service levels, escalation paths, runbooks, change controls, release processes, and on‑call responsibilities. Strong working knowledge of modern data platforms, including Snowflake, S3‑based data lakes, SQL, dbt, managed ingestion tools such as Fivetran or HVR, and custom data pipelines. Understanding of data quality, freshness, lineage, schema evolution, pipeline dependencies, backfills, and recovery procedures. Proficiency in Python, Shell, Bash, or comparable languages for automation and operational tooling. Ability to make well‑reasoned architecture and operational decisions, communicate tradeoffs, estimate work, identify risks, and guide teams through change. Proven experience mentoring engineers, reviewing technical work, delegating ownership, and improving engineering processes across a distributed team. Strong stakeholder‑management and communication skills, including the ability to collect requirements, explain technical risks, and present recommendations to client leaders. Strong written and verbal English communication skills. Availability to work within the LatAm service window of approximately 9:00 AM to 6:00 PM Eastern Time and participate in an agreed senior escalation and on‑call rotation.