Backend Developer - AI Trainer (Spain)

Anyone AI Inc.

Job Overview

Location

Spain

Job Type

Contract

Full Job Description

📋 Description

• Design and implement complex, multi-file coding tasks focused on bug resolution, feature implementation, refactoring, and migration within production-like software environments.
• Write clear, precise natural-language specifications that accurately define coding problems and expected outcomes for AI training purposes.
• Develop and extend comprehensive unit and integration test suites using frameworks such as pytest, Jest, JUnit, xUnit, or Go testing to validate code correctness and edge case handling.
• Create realistic software engineering scenarios that mirror actual production challenges faced by backend and full-stack developers.
• Review peer-generated coding tasks for correctness, clarity, realism, and alignment between specifications and implementation.
• Identify ambiguities, edge cases, potential failure modes, and inconsistencies in code, tests, and documentation provided by other contributors.
• Ensure strict alignment between natural-language task descriptions, reference implementations, and expected system outputs.
• Produce high-quality, production-realistic artifacts including code, tests, and validation materials used to train and evaluate AI models.
• Deliver structured, actionable feedback on peer submissions, highlighting strengths, weaknesses, and opportunities for improvement in code quality and design.
• Work independently on a project-based, part-time basis with full control over schedule and work pace.
• Operate remotely using personal tools and infrastructure; no company-provided equipment or software is provided.
• Collaborate asynchronously with a global team of expert contributors to maintain consistency in task quality and evaluation standards.
• Maintain professional written proficiency in English to ensure clarity and precision in all task specifications, feedback, and documentation.
• Participate in production-scale codebase navigation and debugging of large, complex, multi-file systems.
• Perform code reviews and refactoring exercises that reflect real-world maintenance and modernization efforts in enterprise environments.
• Contribute to the creation of reference implementations that serve as gold-standard examples for AI model training.
• Engage in production migrations and system upgrades as part of scenario design, ensuring tasks reflect current industry practices.
• Deliver robust test coverage and validation artifacts that demonstrate thoroughness in testing functionality, edge cases, and failure recovery.
• Adhere to strict quality benchmarks for task realism, code quality, and instructional clarity to ensure AI models receive high-fidelity training data.

🎯 Requirements

• 3–7 years of professional software engineering experience
• Advanced professional written proficiency in English
• 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

🏖️ Benefits

• Project-based compensation paid per task with rates based on anticipated completion time
• Full flexibility to set own schedule and work remotely
• Ability to work simultaneously with other vendors or employers (subject to their policies)
• No requirement for company-provided tools or equipment — contributors use their own

Skills & Technologies

Python

JavaScript

TypeScript

Java

Backend

Remote

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Anyone AI Inc.

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About Anyone AI Inc.

Anyone AI provides no-code computer-vision infrastructure that lets companies build, train and deploy image and video models without machine-learning teams. Its cloud platform automates data labeling, model optimization and edge deployment for retail, manufacturing, logistics and healthcare use cases. The company offers pre-trained APIs for object detection, counting and anomaly identification, plus dashboards for continuous monitoring and compliance. Founded in 2021, it targets enterprises seeking rapid AI adoption while avoiding costly specialists and infrastructure setup.

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