AI Evaluation Engineer (Python, QA or Security)

AI Evaluation Engineer (Python, QA or Security)

Mindrift
Mindrift
SpainUp to US$70,000RemoteAdded yesterdayMid · 5+ yearsFreelance🇬🇧English: Required

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About the role

Please submit your CV in English and indicate your level of English proficiency.

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.

What this opportunity involves We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.

What you'll do

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 we're looking 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+

What you'll get

Compensation 

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

USD 70,000 per year

How you'll work

remote

About the company & team

Creator (Writer)

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

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 

Application managed by Mindrift