IntelliJ IDEA Coding Workflow Expert

The Work

You will create high-quality coding workflow data to help AI systems understand practical software development in IntelliJ IDEA. This includes setting up realistic projects, documenting each task, recording yourself completing the workflow, and checking the final materials for clarity and completeness.

• Create realistic tasks using Java or Kotlin projects.
• Build workflows involving debugging, project setup, refactoring, testing, Maven or Gradle, Git, code navigation, package management, or build troubleshooting.
• Prepare project files, SDKs, dependencies, and reference materials before recording.
• Review recordings and documentation to make sure they are clear, complete, realistic, and aligned with project guidelines.

What It Pays and Takes

This is independent contractor work for people with hands-on IntelliJ IDEA and software development experience. The role is listed as entry level, but you must already be comfortable with the technical workflows below.

• Pay: Up to $25 per hour.
• Time: 20 or more hours per week.
• Work type: Remote, part-time contract work.
• Location: Bangladesh, India, or Pakistan.
• Language: Strong written English at B2 level or higher.
• Required: Experience with IntelliJ IDEA, Java or Kotlin, backend development, debugging, project setup, refactoring, build tools, or Git workflows.
• You should understand project structure, SDKs, run configurations, the debugger, Maven or Gradle, terminal use, code navigation, and version control.
• You must be able to manage files, install dependencies, configure an SDK, prepare a reliable recording environment, and explain technical workflows clearly.
• Attention to detail, self-direction, and reliable delivery across time zones are required.
• Experience with QA, GitHub, DevOps, technical writing, or similar computer-based workflows is welcome.

How It Works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI Training Work

AI training work is the human side of building artificial intelligence. Contributors prepare examples, review outputs, or demonstrate real workflows so AI systems can learn how people solve practical problems, and experienced contributors are paid for the technical judgment and care this requires.