H

Python Developer - AI Agent Evaluation & LLM Training (Remote)

hire feed • Norway
Remote
This Job is No Longer Active This position is no longer accepting applications

Design and evaluate autonomous AI agents across multiple LLMs for health, education, and daily life domains. Debug agent traces, stress test against edge cases, and provide high-density technical feedback for LLM training. Requires backend engineering experience, proficiency in Python and at least one other major language, and SQL database skills.

Key Highlights
Fully remote role open to candidates in Finland, France, Italy, and Norway
Hourly compensation of USD $30-$50, paid weekly via PayPal or AirTM
Shape the future of agentic AI systems by providing expert human feedback to leading AI organizations
Key Responsibilities
Write evaluation rubrics with objective pass/fail criteria
Debug agent traces to identify failure patterns
Stress test agents against edge cases, prompt injection, and tool misuse
Assess production-grade modular software architecture
Analyze multi-turn system interactions and behaviors
Provide high-density technical feedback for LLM training
Technical Skills Required
Python JavaScript Go Java SQL
Benefits & Perks
Hourly compensation USD $30-$50
Weekly payments via PayPal or AirTM
Fully remote work
Nice to Have
Experience integrating agents with live tools such as Supabase, Gmail, and other APIs
Familiarity with persistent state and session-tracking patterns
Experience identifying privacy leaks, authority escalation, or indirect prompt injection vulnerabilities

Job Description

  • Job Title: Python Developer (Remote)
  • Location: Remote (Finland, France, Italy, Norway)
  • Work Mode: Fully Remote

Role Overview

Help design and evaluate autonomous AI agents across multiple LLMs, spanning health, education, daily life, and other real-world domains (all coding work). Shape the future of agentic AI systems by providing expert human feedback to leading AI organisations. Help train Large Language Models (LLMs) for complex, multi-step architectural workflows.

Key Responsibilities

AI Agent Evaluation

  • Write evaluation rubrics with objective pass/fail criteria
  • Debug agent traces to identify failure patterns
  • Stress test agents against edge cases, prompt injection, and tool misuse
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