Backend Developer (Peru)

Work location: Remote (Peru)

Pay: $45 - $80 per hour, as the posting states it.

Anyone AI is recruiting skilled Backend Developers (Python and JavaScript/TypeScript; working knowledge of Java, C#, or Go) to work on a project with a leading AI Lab.

Qualifications:

- Advanced professional written proficiency in English

- 3-7 years of professional software engineering experience

- Strong proficiency in Python and JavaScript/TypeScript; working knowledge of Java, C#, or Go

- Backend or full‑stack development experience in production systems

- Experience with testing frameworks (e.g., pytest, Jest, JUnit, xUnit, Go testing)

- Proven ability to debug and navigate large, multi‑file codebases

- Experience with code reviews, refactoring, and production migrations

Engagement: Part-time, project-based expert evaluation work

Work Type: Remote

Contributors will design and evaluate realistic software engineering tasks, including bug resolution, feature implementation, refactoring/migration, and test generation. Work includes both creating complex coding scenarios and reviewing peer submissions for quality and accuracy.

This is a project-based consultant role. Consultants will be paid on a per-project basis; hourly rates are estimates based on anticipated completion time. Consultants control their own schedule, provide their own tools, and may simultaneously provide services to other vendors/employers (subject to those vendors’ allowances).

Responsibilities:

Contributors will:

- Design and implement multi-file coding tasks across bug fixing, feature development, refactoring, and testing

- Write clear natural-language specifications and reference implementations

- Develop and extend unit and integration test suites

- Review peer-generated tasks for correctness, clarity, and realism

- Identify edge cases, ambiguities, and potential failure modes

- Ensure alignment between specifications, code, and expected outputs

Expected Outcomes:

- High-quality, production-realistic coding tasks

- Complete and correct reference implementations

- Robust test coverage and validation artifacts

- Structured, actionable peer review feedback