The work
You will support AI agent development by building backend connectors, testing software behavior, creating realistic tasks, and writing rubrics that judge whether an agent's work is correct. The role combines software development, quality checks, data generation, and model evaluation.
The Computer Science (STEM) role may involve different duties and qualifications, so review those details before applying.
- Build Python backends that replicate collaboration, project management, email, documentation, and workflow systems.
- Extend existing connectors and create new ones within agreed timeframes.
- Test connectors against the systems they emulate and validate their behavior.
- Study workflows and data to identify realistic long-horizon tasks for AI agents.
- Write tasks and rubrics covering correct, partly correct, and deficient results.
- Join calibration and quality reviews while meeting agreed quality milestones.
What it pays and takes
This is a remote contractor engagement lasting four weeks and starting immediately. You must complete at least one approved task each day, with no stated cap on the number of tasks.
- Pay: $300 per approved task.
- Time: At least 20 hours per week.
- Location: Remote and open worldwide.
- Language: Fluent in English.
- Experience: At least three years of backend development experience.
- Technical skills: Strong Python with FastAPI, Flask, or Django; scalable backends; REST APIs; and microservices.
- Tools and practices: Git, Docker, pipelines, testing, and code-quality practices.
- AI tools: Daily experience with AI coding assistants such as Claude Code, Codex, Cursor, GitHub Copilot, or similar tools.
- Judgment: Ability to assess software behavior, task realism, correctness, and quality standards precisely.
How it works
Apply on OpenTrain with your resume, then complete the application on the hiring site.
About AI training work
AI training is the human work behind systems that learn from examples. People build and review code, tasks, and model responses so AI systems can behave more reliably, and experienced contributors are valued for their specialist knowledge and careful judgment.