DevOps Engineer (part-time) (Fully Remote)

Aleroy; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive salary

Continuous learning

Job summary

Aleroy is seeking a hands-on DevOps Engineer to build, automate, and operate scalable AI infrastructure. You will own cloud infrastructure, container orchestration, CI/CD, monitoring, and incident response in a small, collaborative team.

Ideal candidates have practical experience with Kubernetes, ArgoCD, GitLab CI, Docker, and Linux, and a passion for secure, reliable deployment at scale in a fast-moving environment. Competitive salary and opportunities for growth.

Qualifications

• Hands-on with Kubernetes, ArgoCD, GitLab CI, Docker, and Linux.
• Experience building scalable cloud infrastructure.
• Knowledge of security, access, secrets, and network best practices.

Responsibilities

• DevOps Engineer to build, automate, and run infrastructure.
• Own cloud infrastructure, container orchestration, CI/CD, monitoring, and incident support.
• Security, access, secrets, and network best practices.

Skills

CI/CD automation

Cloud infrastructure

Monitoring

Incident response

Tools

Kubernetes

ArgoCD

GitLab CI

Docker

Linux

Job description

• Unified platform for high-performance AI inference.
• Small, collaborative teams focused on scalable AI infrastructure.

About the Role:

• DevOps Engineer to build, automate, and run infrastructure.
• Hands-on with Kubernetes, ArgoCD, GitLab CI, Docker, and Linux.

What You Will Own:

• Cloud infrastructure, container orchestration, CI/CD, monitoring, and incident support.
• Security, access, secrets, and network best practices.

What We Offer:

• Small senior team, fast execution, low bureaucracy.
• Competitive salary, performance incentives, and continuous learning.

Aleroy

Aleroy builds a unified platform for high-performance AI inference, enabling companies to deploy and run AI models at scale. The team works in small, collaborative groups focused on solving complex engineering challenges to build reliable, scalable AI infrastructure.