Evaluation Scenario Writer - AI Agent Testing Specialist at Mindrift

Warsaw, Masovian Voivodeship, Poland -

Full Time

Start Date

Immediate

Expiry Date

22 Mar, 26

Salary

30.0

Posted On

22 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Evaluation Scenarios, LLM-based Agents, Test Cases, Analytical Mindset, Attention to Detail, AI Decision Making, Test Design Principles, Written Communication, JSON, YAML, Python, JavaScript, NLP, Data Analysis, QA, Software Testing

Industry

technology;Information and Internet

Description

This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English. At Mindrift, innovation meets opportunity. We believe in using the power of collective human intelligence to ethically shape the future of AI. What we do The Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe. About the Role We’re looking for someone who can design realistic and structured evaluation scenarios for LLM-based agents. You’ll create test cases that simulate human-performed tasks and define gold-standard behavior to compare agent actions against. You’ll work to ensure each scenario is clearly defined, well-scored, and easy to execute and reuse. You’ll need a sharp analytical mindset, attention to detail, and an interest in how AI agents make decisions. Although every project is unique, you might typically: Create structured test cases that simulate complex human workflows. Define gold-standard behavior and scoring logic to evaluate agent actions. Analyze agent logs, failure modes, and decision paths. Work with code repositories and test frameworks to validate your scenarios. Iterate on prompts, instructions, and test cases to improve clarity and difficulty. Ensure that scenarios are production-ready, easy to run, and reusable. How to get started Simply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you’ll help shape the future of AI while ensuring technology benefits everyone. Bachelor's and/or Master’s Degree in Computer Science, Software Engineering, Data Science / Data Analytics, Artificial Intelligence / Machine Learning, Computational Linguistics / Natural Language Processing (NLP), Information Systems or other related fields. Background in QA, software testing, data analysis, or NLP annotation. Good understanding of test design principles (e.g., reproducibility, coverage, edge cases). Strong written communication skills in English. Comfortable with structured formats like JSON/YAML for scenario description. Can define expected agent behaviors (gold paths) and scoring logic. Basic experience with Python and JS. Curious and open to working with AI-generated content, agent logs, and prompt-based behavior. Nice to Have Experience in writing manual or automated test cases. Familiarity with LLM capabilities and typical failure modes. Understanding of scoring metrics (precision, recall, coverage, reward functions). Contribute on your own schedule, from anywhere in the world. This opportunity allows you to: Get paid for your expertise, with rates that can go up to $30/hour depending on your skills, experience, and project needs. Take part in a flexible, remote, freelance project that fits around your primary professional or academic commitments. Participate in an advanced AI project and gain valuable experience to enhance your portfolio. Influence how future AI models understand and communicate in your field of expertise.

How To Apply:

Incase you would like to apply to this job directly from the source, please click here

Responsibilities

The role involves designing realistic evaluation scenarios for LLM-based agents and creating test cases that simulate human tasks. The candidate will also analyze agent logs and ensure scenarios are production-ready and reusable.