We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks. You'll create challenging tasks and evaluation criteria within realistic simulated environments:

Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history

Design tasks from intermediate states of these environments - craft the prompt, define what "solved" means, and ensure the task is solvable by an AI agent

Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient

Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust

What this is NOT

Not data labeling

Not prompt engineering

Not writing code from scratch - the agent writes most of the code; you guide and evaluate

What we look for

5+ years in software development

Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis

Experience writing tests (functional, integration)

English proficiency - B2+

Why this is hard

Frontier models are already good at coding. Creating a task that genuinely challenges the best models is non-trivial. You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution.

Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.

How it works

Apply

Pass qualification(s)

Join a project

Complete tasks

Get paid

Compensation

Up to $40/hr equivalent , depending on level and pace. Tasks are estimated at ~20 hours each; you set your own schedule.

Desired Candidate Profile

• 5+ years in software development
• Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis
• Experience writing tests (functional, integration)
• English proficiency - B2+