10 ott - Italia
Anyone AI
pAnyone AI is recruiting skilled software engineers who also speak Italian, to work on a project with a leading AI Lab. /ph3Qualifications: /h3ulliAdvanced professional written proficiency in English /lili3–7 years of professional software engineering experience /liliStrong proficiency in Python and JavaScript/TypeScript; working knowledge of Java, C#, or Go /liliBackend or full‑stack development experience in production systems /liliExperience with testing frameworks (e.g., pytest, Jest, JUnit, xUnit, Go testing) /liliProven ability to debug and navigate large, multi‑file codebases /liliExperience with code reviews, refactoring, and production migrations /li /ulh3Engagement: /h3pPart-time, project-based expert evaluation work /ph3Work Type: /h3pRemote /ppContributors 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. /ppThis 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). /ph3Responsibilities: /h3pContributors will: /pulliDesign and implement multi-file coding tasks across bug fixing, feature development, refactoring, and testing /liliWrite clear natural-language specifications and reference implementations /liliDevelop and extend unit and integration test suites /liliReview peer-generated tasks for correctness, clarity, and realism /liliIdentify edge cases, ambiguities, and potential failure modes /liliEnsure alignment between specifications, code, and expected outputs /li /ulh3Expected Outcomes: /h3ulliHigh-quality, production-realistic coding tasks /liliComplete and correct reference implementations /liliRobust test coverage and validation artifacts /liliStructured, actionable peer review feedback /li /ul #J-18808-Ljbffr
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