Job description
***This opportunity is intended for experienced Senior Python Engineers only****
Open to candidates in the North America, South America, Asia and Europe.
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.
You'll create challenging tasks and evaluation criteria within realistic simulated environments:
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Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history
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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
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Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient
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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
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Not data labeling
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Not prompt engineering
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Not writing code from scratch - the agent writes most of the code; you guide and evaluate
What we look for - You must meet all the requirements in order to be considered for this project:
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5+ years of professional experience with Python.
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Strong experience with FastAPI, pytest, and async/await.
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Hands-on experience with Docker, PostgreSQL, and CI/CD pipelines.
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Proven experience writing and maintaining automated tests (not just executing them).
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Full-stack experience with React and TypeScript is a plus.
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English proficiency at B2 level or higher.
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Availability to work 30+ hours per week.
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
The process is designed to move quickly and typically includes the following steps:
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App review and invitation to a virtual project introduction session (approximately 30 minutes)
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Platform registration and identity verification
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Technical assessment (approximately 35 minutes)
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Background check (completed at no cost to candidates)
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Onboarding and project-specific training tasks
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Begin production work!
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Willingness to complete identity verification as part of the onboarding process.
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Ability to complete a technical assessment.
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Willingness to join and participate in Discord, which will be used for project communication and updates.
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Successful completion of a background check is required prior to onboarding.
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Reliable internet connection and ability to communicate effectively in a remote environment.
