Cloud Engineer – DevOps/SRE with AI Coding Agent Experience

About the role

Contributors help evaluate and improve frontier AI coding models through structured technical assessments. The work focuses on realistic infrastructure engineering workflows and model evaluation. Spots are limited and filled on a first‑come, first‑served basis.

Key responsibilities

• Use frontier AI coding agents to complete and evaluate complex infrastructure engineering tasks.
• Review model‑generated implementations involving cloud platforms, Kubernetes, CI/CD systems, observability, and infrastructure automation.
• Identify bugs, edge cases, reliability issues, and failure modes in model outputs.
• Compare outputs from multiple frontier models and assess their strengths and weaknesses.
• Apply professional engineering judgment to realistic infrastructure engineering scenarios.

Required profile

• 2+ years of professional DevOps, SRE, or Cloud Engineering experience.
• Experience with AWS, Azure, GCP, Kubernetes, Terraform, CI/CD pipelines, or observability tooling.
• Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
• Ability to evaluate model‑generated infrastructure and reliability engineering solutions.
• Experience supporting production‑scale systems is preferred.

Required skills

• AWS
• Azure
• Google Cloud Platform (GCP)
• Kubernetes
• Terraform
• CI/CD pipelines
• Observability tooling
• AI coding agents (Cursor, Claude Code, Codex, Windsurf, Gemini CLI)

What we offer

• Compensation of $400 per accepted task (approximately $85 per hour).
• Typical tasks take 2‑3 hours after ramp‑up.
• Sprint‑based projects running in 12‑24 hour stretches.
• Fully remote, freelance engagement.