**Role & seniority: ** AI Quality Engineer (contract/part-time style via flexible assignments); seniority not explicitly stated (requires production engineering experience).

**Stack/tools: **

Languages: Python, JavaScript, Go, or Java (at least two)
SQL databases
Multi-LLM agent evaluation/tracing
Optional: agent integrations with Supabase, Gmail, and third-party APIs
Handles “live, non-mocked” environments
Top 3 responsibilities:
1. Evaluate AI agents: write objective rubrics with pass/fail criteria; analyze agent traces to identify failure patterns.
2. Stress test agents: cover edge cases, prompt injection, and tool misuse; verify correct tool use and behavior.
3. Provide technical assessments for LLM training: review modular/production-grade architecture, analyze multi-turn interactions, give high-density training feedback.
Must-have skills:
- Backend engineering or AI automation/complex systems integration experience
- Ability to build/maintain production-grade modular software (separate concerns/services like parsing, logic, reporting)
- Strong command of 2+ major languages and SQL
- Experience with real/live environments and multi-turn system behavior debugging
Nice-to-haves:
- Integrating agents with live tools/APIs (Supabase, Gmail, etc.)
- Persistent state / session-tracking patterns
- Security/privacy issue detection: **priv

Full Description

Job Title: AI Quality Engineer (Remote)

Location: Remote (United States, Canada, United Kingdom, Australia)

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 Technical Assessment Assess production-grade modular software architecture Analyse multi-turn system interactions and behaviours Provide high-density technical feedback for LLM training Project Workflow Create an account and upload a resume/ID Complete the onboarding assessment Start earning through flexible task assignments

Qualifications Experience in backend engineering, AI automation, or complex systems integration Proven ability to build and maintain production-grade software with modular separation (e.g., distinct services for data parsing, logic processing, and reporting) Strong command of at least two major languages (e.g., Python, JavaScript, Go, or Java) and experience working with SQL databases Practical experience building for live, non-mocked environments and handling multi-turn system interactions

Preferred (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

Compensation Hourly compensation ranges from USD $30–$50, depending on experience and task complexity Payments are issued weekly via supported payout platforms (e.g., PayPal or AirTM) Full compensation details are provided prior to task acceptance

Equal Opportunity Statement Selection decisions are based solely on skills, qualifications, and project requirements. We are committed to inclusive and fair engagement practices and consider all qualified applicants without regard to legally protected characteristics.

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