Backend Developer (Ecuador)

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