Software Engineering AI Trainer (Chile)
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- Chile, Chile
- Chile
Resumen del puesto por JobGrid
Software Engineering AI Trainer (Chile) at anyone-ai: Chile, Chile, Chile; Presencial. This listing is part of JobGrid's Empleos de software engineer en páginas de empresas. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.
- Location and workplace: Chile, Chile, Chile, Presencial
- Source freshness: checked by JobGrid on 2026-06-05.
- Application path: candidates continue to the employer application page with non-personal referral tags.
Anyone AI is recruiting skilled software engineers 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