Remote DevOps Engineer — CI/CD, Kubernetes & IaC

YO AI Labs; Seattle (WA); Remote; USD 83,000 - 124,000; Full time

Job summary

YO AI Labs is seeking an experienced DevOps Engineer for a remote contractor role. You will work on production-style infrastructure and automation for AI systems, focusing on CI/CD, Kubernetes, IaC, Linux, and cloud environments.

Prior AI experience is not required; strong DevOps engineering judgment matters most. Key tasks include designing DevOps tasks, creating reference solutions, reviewing AI-generated outputs, and ensuring correctness and reproducibility.

Qualifications

• 3+ years of professional experience in DevOps, SRE, Platform, or Infrastructure Engineering.
• Strong coding skills in Python, Go, Bash, or TypeScript.
• Hands-on experience with CI/CD tools such as GitHub Actions, GitLab CI, or Jenkins.
• Practical experience with Docker, Kubernetes, and at least one major cloud platform.
• Infrastructure as Code experience with Terraform, Ansible, Pulumi, or CloudFormation.
• Advanced Linux and Git skills.
• Strong written and spoken English.
• Availability of at least 20 hours per week.

Responsibilities

• Design realistic DevOps tasks covering CI/CD, containers, Kubernetes, IaC, monitoring, and incident response.
• Create working reference solutions with clear setup and validation steps.
• Review AI-generated solutions, identify failures, and provide precise technical corrections.
• Maintain high standards for correctness, reliability, and reproducibility.
• Provide structured feedback to improve AI-generated DevOps workflows.

Skills

Kubernetes

Terraform

CI/CD

Python

Linux

Docker

Git

Cloud Platforms

Infrastructure as Code

Job description

YO AI Labs is seeking an experienced DevOps Engineer for a remote contractor role. You will work on production-style infrastructure and automation for AI systems, focusing on CI/CD, Kubernetes, IaC, Linux, and cloud environments.

Prior AI experience is not required; strong DevOps engineering judgment matters most. Key tasks include designing DevOps tasks, creating reference solutions, reviewing AI-generated outputs, and ensuring correctness and reproducibility.