About this role
Role Overview
This role supports a Frontier Code Agents initiative at a leading AI research lab, focused on evaluating and improving advanced AI coding models by performing structured technical assessments of realistic infrastructure engineering workflows and model outputs.
Key Responsibilities- Use frontier AI coding agents to perform and evaluate complex infrastructure engineering tasks.
- Review model-generated implementations that involve cloud platforms, Kubernetes, CI/CD systems, observability, and infrastructure automation.
- Identify bugs, edge cases, reliability problems, and likely failure modes in model outputs.
- Compare outputs from multiple frontier models, assessing relative strengths and weaknesses.
- Apply professional engineering judgment to realistic infrastructure and reliability engineering scenarios.
- Minimum 2 years of professional experience in DevOps, SRE, or Cloud Engineering.
- Hands-on experience with one or more cloud platforms, such as AWS, Azure, or GCP.
- Familiarity with Kubernetes, Terraform, CI/CD pipelines, and 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.
- Remote role.
- Hourly engagement, sprint based, with project sprints running in 12 to 24 hour stretches depending on client requirements.
- Spots are limited and are filled on a first come, first serve basis.
- $400 paid per accepted task.
- Typical tasks take approximately 2 to 3 hours of work after ramp-up.
- Compensation is tied to accepted work.
- Metadata indicates an hourly reference rate of $85 per hour.
- Role is open to remote applicants. No specific work authorization or sponsorship information was provided in the source; applicants should confirm they are eligible to work in their location.