DevOps Engineer - AI Model Evaluator

mercor; United States; Remote; USD 96,000 - 138,000; Full time

Job summary

Mercor is seeking a DevOps/SRE/Cloud Engineer (Coding Agent Experience) for remote contract work. You will work with frontier AI coding agents to execute complex infrastructure tasks and review model-generated infrastructure across AWS, GCP, Azure, Kubernetes, and CI/CD pipelines.

The role emphasizes evaluating model outputs, identifying reliability issues, and applying engineering judgment to real-world scenarios in a remote setting.

Qualifications

• 2+ years of professional DevOps, SRE, or Cloud Engineering experience.
• Experience with AWS, Azure, GCP, Kubernetes, Terraform, CI/CD, or observability tooling.
• Ability to evaluate model-generated infrastructure and reliability engineering solutions.

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, 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.

Skills

DevOps/SRE/Cloud

Tools

AWS

Azure

GCP

Kubernetes

Terraform

CI/CD pipelines

Observability tooling

Job description

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: Remote

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 , 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.