Software Developer (Mexico, Colombia, Ecuador, Peru, Argentina)
At Anyone AI · Argentina - Fully Remote; Buenos Aires, Distrito Federal, Argentina
Salary: US$45–80 an hour
- Engineering
- Contract
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Open to Argentina
“Argentina - Fully Remote”
From the location.
“Buenos Aires, Distrito Federal, Argentina”
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- Posted
- 13 July 2026
- First seen by us
- 10 October 2026
- Last checked
- 7 hours ago
Job description
From Anyone AI’s job post, as they wrote it.
Anyone AI is recruiting skilled Backend Developers to work as a project consultants.
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)
Read the full description
* 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
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