AI Evaluation Engineer (Python, QA or Security)

Mindrift

Michigan

On-site

USD 41,000 - 69,000

Full time

14 days+

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Job summary

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focusing on testing, evaluating, and improving AI systems. This role involves creating realistic developer environments and designing tasks to evaluate AI coding agents, with emphasis on robust, flexible testing methods.

We are looking for someone with 5+ years in software development and a core stack including Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, and Redis, plus

Qualifications

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

Responsibilities

  • 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.

Skills

Python
JavaScript/TypeScript
Docker
Postgres
Kafka
Redis
Testing
English (B2+)

Job description

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.

Compensation

Up to $50/hr equivalent, depending on level and pace. Tasks are estimated at ~20 hours each; you set your own schedule.

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