Role & seniority
- AI Automation Engineer (evaluation/training-focused, not managerial)
- Senior level not explicitly stated; requires production engineering experience
Stack/tools
- Programming languages: Python, JavaScript, Go, or Java (at least two preferred)
- Data: SQL databases
- Agent/LLM work: evaluation rubrics, debugging agent traces, multi-turn workflow assessment
- Nice-to-have integrations: Supabase, Gmail, other APIs
Top 3 responsibilities
- Evaluate autonomous AI agents: write objective pass/fail rubrics, debug traces, identify failure patterns
- Stress test agent robustness: edge cases, prompt injection, and tool misuse
- Provide technical assessment for LLM training: review modular architecture, analyze multi-turn behaviors, deliver high-density feedback
Must-have skills
- Backend engineering / AI automation / complex systems integration experience
- Ability to build and maintain production-grade modular software (separation of concerns such as parsing vs logic vs reporting)
- Strong proficiency in 2+ major languages and SQL
- Experience working against live/non-mocked environments and handling multi-turn interactions
Nice-to-haves
- Agent integrations with live tools/APIs (e.g., Supabase, Gmail)
- Persistent state/session-tracking patterns
- Security evaluation skills: detecting privacy leaks, authority escalation, indirect prompt inj

Full Description

Job Title: AI Automation 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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