Evaluation Scenario Writer - AI Agent Testing Specialist

Mindrift

United Kingdom

Remote

GBP 25,628 - 51,257

Part time

14 days+

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Benefits offered by this job

Competitive hourly rates

Flexible work schedule

Experience in an advanced AI project

Job summary

A leading AI consulting firm in the United Kingdom is currently seeking to fill an entry-level position focused on designing evaluation scenarios for LLM-based agents. This role requires analytical skills to create test cases that mirror complex human workflows. Ideal candidates will possess a relevant degree and some experience in QA or data analysis. The position offers a part-time schedule, with rates reaching up to $50/hour, along with a flexible, remote work environment.

Qualifications

Bachelor's or Master's Degree in a relevant field.
Background in QA, software testing, data analysis, or NLP annotation.
Good understanding of test design principles.
Strong written communication skills in English.
Comfortable with structured formats like JSON/YAML.
Can define expected agent behaviors and scoring logic.
Basic experience with Python and JS.
Curious about AI-generated content and agent logs.

Responsibilities

Design realistic evaluation scenarios for LLM-based agents.
Create structured test cases that simulate human workflows.
Define gold-standard behavior and scoring logic.
Analyze agent logs and decision paths.
Work with code repositories to validate scenarios.
Iterate on prompts and test cases for clarity.

Job 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.

What We Do

At Mindrift, innovation meets opportunity. We believe in using the power of collective human intelligence to ethically shape the future of AI. 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.

Requirements

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)

Benefits

Get paid for your expertise, with rates that can go up to $50/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

Seniority level