DevOps Engineer - AI Model Evaluator

mercor; Schweiz; À distance; CHF 82 000 - 112 000; Plein temps

Résumé du poste

mercor is seeking a DevOps/SRE/Cloud Engineer (Coding Agent Experience) for remote, contract work. You will leverage frontier AI coding agents to tackle complex infrastructure tasks and review model-generated implementations across cloud platforms, Kubernetes, and CI/CD pipelines.

You will identify reliability issues, compare outputs from several frontier models, and apply professional engineering judgment to realistic infrastructure scenarios.

Qualifications

• 2+ years of professional DevOps/SRE/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.

Responsabilités

• 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.

Connaissances

DevOps

SRE

Cloud engineering

AI tooling literacy

Outils

AWS

Azure

GCP

Kubernetes

Terraform

CI/CD

Observability tooling

Cursor

Claude Code

Codex

Windsurf

Gemini CLI

Description du poste

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.