Requirements
3-7 years of professional software engineering experience with strong proficiency in Python and JavaScript/TypeScript. Experience with Java, C#, or Go, backend or full-stack development in production systems, and testing frameworks (e.g., pytest, Jest, JUnit, xUnit, Go testing) is required. Proven ability to debug large codebases and experience with code reviews, refactoring, and production migrations are essential.
Description
Anyone AI is recruiting skilled Backend Developers to work as a project consultants.Qualifications:Advanced professional written proficiency in English3–7 years of professional software engineering experienceStrong proficiency in Python and JavaScript/TypeScript; working knowledge of Java, C#, or GoBackend or full‑stack development experience in production systemsExperience with testing frameworks (e.g., pytest, Jest, JUnit, xUnit, Go testing)Proven ability to debug and navigate large, multi‑file codebasesExperience with code reviews, refactoring, and production migrationsEngagement: Part-time, project-based expert evaluation workWork Type: RemoteContributors 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 testingWrite clear natural-language specifications and reference implementationsDevelop and extend unit and integration test suitesReview peer-generated tasks for correctness, clarity, and realismIdentify edge cases, ambiguities, and potential failure modesEnsure alignment between specifications, code, and expected outputsExpected Outcomes:High-quality, production-realistic coding tasksComplete and correct reference implementationsRobust test coverage and validation artifactsStructured, actionable peer review feedback