React and Next.js AI Code Review Engineer

You will review AI-generated frontend code, technical explanations, and architectures built with React and Next.js. You will also create reference implementations and model answers that show accurate, clear, and maintainable solutions.

• Check React and Next.js code for correctness, readability, accessibility, security, and performance.
• Find problems with rendering, state management, routing, data fetching, hydration, caching, and bundle size.
• Write reference answers, explanations, and model solutions for advanced frontend questions.
• Compare AI responses and rate their reasoning, technical accuracy, and use of best practices.
• Create prompt content about React and Next.js for AI training work.
• Fact-check technical details and help improve AI-generated engineering content.

This is an hourly, part-time contractor role for an intermediate-level professional. The work is fully remote and conducted in English.

• Pay: $60 to $90 USD per hour.
• Time: 20+ hours per week.
• Location: Candidates must be based in the United States, Germany, or India.
• Language: English.
• Strong professional experience with React and Next.js, including modern React patterns and Next.js App Router concepts.
• Deep knowledge of HTTP, browser rendering, security basics, cookies, sessions, and OAuth flows.
• Practical experience with Jest, Vitest, React Testing Library, Playwright, Cypress, linting, and CI/CD.
• Experience with code review, performance optimization, accessibility, and clear technical writing in English.
• Experience with SSR, SSG, ISR, Server Components, middleware, caching, and deployment patterns is helpful.
• Familiarity with keyboard navigation, ARIA, focus management, semantic HTML, and contrast standards is helpful.
• Experience building production React applications at scale is helpful.
• Prior AI training, annotation, or evaluation experience is a strong plus.

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

AI training work is the human side of building artificial intelligence. Specialists review examples, rate model responses, write better answers, and check technical accuracy so AI systems learn to produce more useful results.