Ai Evaluation Engineer (Python, Qa Or Security)

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: 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.

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: 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.

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.