Mindrift

FreelanceAgentEvaluationEngineer

Mexico; India PART TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Freelance Agent Evaluation Engineer at Mindrift. Skills: Python, Software development, Test automation, AI system evaluation, Task design, Evaluation criteria definition. Create challenging tasks for AI coding agents. Define evaluation criteria for AI coding agents”

What You'll Achieve.

Create tasks that genuinely challenge the best AI models; Write tests that accept all correct solutions and reject incorrect ones; Ensure tasks are solvable and evaluations are fair

Industry & Context.

Problems you'll solve

Analyze why an agent failed or succeeded; Design edge cases and adversarial scenarios; Deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution

What They're Looking For.

Must Have

Degree in Computer Science, Software Engineering, or related fields, 5+ years in software development, Primarily Python (FastAPI, pytest, async/await, subprocess, file operations), Background in full-stack development, Experience building React-based interfaces (JavaScript/TypeScript), Experience building robust back-end systems, Experience writing tests (functional, integration), Docker containers, Familiarity with infrastructure tools (Postgres, Kafka, Redis), CI/CD understanding (GitHub Actions as a user: triggers, labels, reading results), English proficiency - B2

Nice to Have

Expert in every item is not required, but comfort reading and reasoning about code across the stack

What You'll Do.

Create challenging tasks for AI coding agents

Define evaluation criteria for AI coding agents

Build virtual companies with codebase

Assemble and calibrate tasks from intermediate states of the virtual company

Craft prompts for AI agents

Design tasks set in isolated environments (emulations of a developer's workstation)

Write tests that accept all correct solutions and reject incorrect ones

Iterate with an AI agent on tests

Review code written by agents

Analyze agent performance

Design edge cases and adversarial scenarios

Iterate based on feedback from expert QA reviewers

How You'll Work.

Team & Collaboration

Iterate based on feedback from expert QA reviewers

Communication Scope

English proficiency - B2

Full Job Description

_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 virtual companies following a high-level plan - codebase, infrastructure, and context (conversations, documentation, tickets) that form a realistic environment with development history * Assemble and calibrate tasks from intermediate states of the virtual company: craft the prompt, define evaluation criteria, and ensure the task is solvable and the evaluation is fair * Design tasks set in isolated environments - emulations of a developer's workstation: a Linux machine with development tools (terminal, CLI), MCP servers (repository, task tracker, messenger, documentation, etc.), and a real web application codebase * Write tests that accept all correct solutions and reject incorrect ones - neither too strict (breaking on valid approaches) nor too lenient (passing bad ones) * Iterate with an AI agent on tests - verifying they catch real problems, don't miss bad solutions, and don't break on good ones * Review code written by agents, analyze why an agent failed or succeeded, and design edge cases and adversarial scenarios * Iterate based on feedback from expert QA reviewers who score your work on quality criteria **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 A significant part of the work is done together with AI - it's very hard to create tasks that challenge frontier models without using frontier models. ### **What we look

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