DevOps / SRE / Cloud Engineer (Coding Agent Experience)

aitrainer; Deutschland; Vor Ort; EUR 43.066 - 68.906; Teilzeit

Zusammenfassung

Aitrainer is looking for experienced professionals in Germany to evaluate frontier AI coding models for complex infrastructure engineering tasks. You'll leverage tools like AWS and Kubernetes while assessing model outputs and identifying potential issues.

This flexible role offers compensation of $400 per accepted task, aiming for candidates with over 2 years in DevOps, SRE, or Cloud Engineering. Join us in shaping the future of AI!

Qualifikationen

• 2+ years of professional DevOps, SRE, or Cloud Engineering experience.
• Ability to evaluate model-generated infrastructure and reliability engineering solutions.
• Experience supporting production-scale systems is preferred.

Aufgaben

• Use frontier AI coding agents to complete and evaluate complex infrastructure engineering tasks.
• Identify bugs and reliability issues in model-generated implementations.
• Apply professional engineering judgment to infrastructure scenarios.

Kenntnisse

DevOps

SRE

Cloud Engineering

Kubernetes

Terraform

CI/CD pipelines

AWS

Azure

GCP

Observability tooling

Tools

Cursor

Claude Code

Codex

Windsurf

Gemini CLI

Jobbeschreibung

About the Role

• Mercor is partnering with a leading AI research lab to support a Frontier Code Agents project.
• Contributors help evaluate and improve frontier AI coding models through structured technical assessments.
• The work focuses on realistic infrastructure engineering workflows and model evaluation.
• Spots are limited and filling quickly on a first come, first serve basis.

What You'll Do

• 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.
• Compare outputs from multiple frontier models and assess their strengths and weaknesses.
• Apply professional engineering judgment to realistic infrastructure engineering scenarios.

Time Commitment

• Sprint based project that runs in 12-24 hour stretches based on client requirement.

Compensation

• $400 per accepted task.
• Typical tasks take approximately 1–3 hours after ramp-up.
• No fixed task limits.
• Compensation is tied to accepted work.

Who Should Apply

• 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.
• Experience supporting production-scale systems is preferred.

We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.