DevOps Engineer - AI Model Evaluator

mercor; Italia; Remote; EUR 88,000 - 120,000; Full time

Job summary

Mercor is seeking a DevOps / SRE / Cloud Engineer (Coding Agent Experience) for a remote contract role. You will use frontier AI coding agents to tackle infrastructure tasks across cloud platforms, Kubernetes, CI/CD, observability, and infrastructure automation, while evaluating model outputs for reliability.

Responsibilities include reviewing model-generated implementations, identifying edge cases and failure modes, and comparing outputs from multiple frontier models to guide engineering

Qualifications

• 2+ years of professional DevOps, SRE, or cloud engineering experience.
• Experience with AWS, Azure, or GCP and Kubernetes.
• 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 solutions.

Responsibilities

• Use frontier AI coding agents to complete and evaluate complex infrastructure tasks.
• Review model-generated implementations involving cloud platforms, Kubernetes, CI/CD, observability, and infra 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 Engineering

Tools

AWS

Azure

GCP

Kubernetes

Terraform

CI/CD

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

Role 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 to assess their 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 such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
• Ability to evaluate model-generated infrastructure and reliability engineering solutions.

Preferred

• Experience supporting production-scale systems.

Compensation & Legal

$400 per accepted task

Compensation tied to accepted work.

Application Process (Takes 20–30 mins to complete)

• Upload resume
• AI interview based on your resume
• Submit form

Resources & Support

• For details about the interview process and platform information, please check:
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PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.