JavaScript Quality Assurance Lead

You will lead quality reviews for JavaScript AI training projects. The work includes checking AI-generated code, debugging responses, explanations, tests, algorithms, frontend and backend snippets, and step-by-step reasoning.

• Review JavaScript code for correctness, runtime behavior, debugging accuracy, readability, maintainability, performance, security, test coverage, formatting, and instruction-following.
• Evaluate trainer and QA submissions against project guidelines and detailed rubrics.
• Check closures, scope, hoisting, prototypes, promises, async and await, event loop behavior, modules, DOM manipulation, and error handling.
• Identify incorrect logic, code that will not run, missing edge cases, insecure recommendations, and incomplete explanations.
• Give precise written feedback on async logic, browser and Node.js differences, security, performance, and readability.
• Spot recurring quality issues and communicate workflow changes and quality expectations to trainers and QAs.
• Maintain style guides, trackers, FAQs, calibration tasks, onboarding materials, and other project documentation.
• Support onboarding and training for remote contributors and help keep contributor activity aligned with project needs.

This is an intermediate, part-time contractor role for someone with professional experience in JavaScript development, code review, software QA, technical mentoring, or related work.

• $70 per hour.
• 20+ hours per week.
• Remote work open to candidates in the United States.
• Strong English communication skills for written technical feedback and team coordination.
• Strong JavaScript expertise, including closures, scope, hoisting, prototypes, promises, async and await, event loop behavior, modules, DOM manipulation, and error handling.
• Comfort with tools and environments such as Node.js, React, Vue, Express, Jest, Mocha, Playwright, ESLint, Prettier, GitHub, and project trackers.
• Helpful background includes leading or supporting remote teams of trainers, reviewers, engineers, technical writers, or QAs.
• Experience with AI training, data annotation, prompt or response evaluation, code content QA, or rubric-based LLM evaluation is helpful.
• Familiarity with calibration tasks, documentation standards, and workflow quality processes is helpful.

Apply on OpenTrain with your resume, then complete the application on the hiring site.

AI training is the human work behind systems that generate and understand code, text, images, and other content. People review examples and model responses so these systems become more accurate, useful, and reliable; OpenTrain helps people find these roles and apply through one profile.