AI Evaluation Engineer (Python, QA or Security)
Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.
About the role
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
Requirements
- 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.
Pay
Up to $50/hr equivalent, depending on level and pace. Tasks are estimated at 20 hours each; you set your own schedule.