Ai Capable Devops Engineer - Model Evaluator (Remote) - $85 An Hour - Remote
Posted Updated
Summary
Contract role (via Mercor for AI labs) evaluating frontier AI coding agents on infrastructure tasks: reviewing model-generated cloud, Kubernetes, and CI/CD implementations to find bugs, edge cases, and reliability issues, and comparing outputs across models. Pays $85/hour ($400 per accepted task), remote.
About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey .Position: DevOps / SRE / Cloud Engineer (Coding Agent Experience) Type: Contract Compensation: $85/hour Location: RemoteResponsibilities
Use frontier AI coding agents to complete and evaluate complex infrastructure engineering tasks.Review model-generated implementations involving cloud platforms, Kubernetes, CI/CD systems, and infrastructure automation .Identify bugs, edge cases, reliability issues, and failure modes in model outputs.Compare outputs from multiple frontier models to assess strengths and weaknesses.Apply professional engineering judgment to realistic infrastructure engineering scenarios.Qualifications Must-Have
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 like Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.Ability to evaluate model-generated infrastructure and reliability engineering solutions.Qualifications Preferred
Experience supporting production-scale systems .Compensation & Legal
$400 per accepted task .Compensation is tied to accepted work.
Use frontier AI coding agents to complete and evaluate complex infrastructure engineering tasks.Review model-generated implementations involving cloud platforms, Kubernetes, CI/CD systems, and infrastructure automation .Identify bugs, edge cases, reliability issues, and failure modes in model outputs.Compare outputs from multiple frontier models to assess strengths and weaknesses.Apply professional engineering judgment to realistic infrastructure engineering scenarios.Qualifications Must-Have
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 like Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.Ability to evaluate model-generated infrastructure and reliability engineering solutions.Qualifications Preferred
Experience supporting production-scale systems .Compensation & Legal
$400 per accepted task .Compensation is tied to accepted work.