Senior DevOps Engineer - Remote Global Infra (Kubernetes)

Devlane; Bogotá; Remote; COP 284,783,000 - 411,353,000; Full time

Benefits offered by this job

Salary in USD

Remote from Home

25 days paid time off

8-hour workday, flexible hours

Welcome kit

High-end hardware provided

English classes

Bonuses

Job summary

Devlane is a dynamic software development company specializing in staff augmentation across Latin America. As a DevOps Engineer, you will join a collaborative team supporting internal infrastructure and modernizing CI/CD pipelines, with a focus on Kubernetes and Linux.

This remote role is open to candidates in Latin America. You’ll work with Engineering, QA, Product, and Support, automate environments, and contribute to scalable infrastructure for AI/data initiatives.

Qualifications

• 5+ years in DevOps, SRE or infrastructure engineering.
• Strong Kubernetes and Linux administration experience.
• Cloud experience with AWS/Azure/GCP/OVH and networking fundamentals.
• Experience with Docker, Helm, ArgoCD, Terraform and CI/CD pipelines.
• Programming in Python or Go and Bash scripting.
• Familiar with monitoring tools like Grafana and Prometheus and databases.
• Fluent English for international teamwork.

Responsibilities

• Build and maintain development and testing environments.
• Improve CI/CD pipelines and automate deployment processes.
• Support modernization of infrastructure during product transitions.

Skills

Kubernetes

Linux administration

Cloud platforms

Networking fundamentals

CI/CD pipelines

Docker

ArgoCD

Terraform

Python/Go scripting

Grafana/Prometheus

Tools

Helm

ArgoCD

Terraform

Grafana

Prometheus

PostgreSQL

Job description

Devlane is a dynamic software development company specializing in staff augmentation across Latin America. As a DevOps Engineer, you will join a collaborative team supporting internal infrastructure and modernizing CI/CD pipelines, with a focus on Kubernetes and Linux.

This remote role is open to candidates in Latin America. You’ll work with Engineering, QA, Product, and Support, automate environments, and contribute to scalable infrastructure for AI/data initiatives.