JavaScript Quality Assurance Lead (QAL)

About the Role

This is a remote, hourly contractor role for a JavaScript Quality Assurance Lead (QAL) responsible for overseeing quality, consistency, and contributor performance across JavaScript AI training projects.

You will review AI-generated JavaScript code, evaluate trainer and reviewer work, provide detailed technical feedback, maintain project documentation, support onboarding, and ensure contributors consistently follow coding, evaluation, and quality standards.

This role combines JavaScript expertise, software engineering review, quality assurance leadership, contributor management, documentation, training, and AI evaluation.

Key Responsibilities

Quality Monitoring

• Review JavaScript AI training items and QA outputs
• Identify quality issues and recurring error patterns
• Provide detailed technical feedback to trainers and reviewers
• Escalate recurring or critical quality concerns

Code Review

Evaluate AI-generated JavaScript implementations, debugging solutions, algorithmic solutions, frontend code, backend code, unit tests, technical explanations, and step-by-step reasoning.

Verify code correctness, runtime behavior, maintainability, readability, security awareness, and performance considerations.

Trainer & QA Communication

• Communicate project updates and guideline changes
• Explain JavaScript-specific review standards
• Ensure contributors remain aligned with project requirements

Question Resolution

Respond to contributor questions regarding JavaScript behavior, async programming, event loop behavior, browser vs Node.js environments, framework usage, testing practices, package management, and rubric interpretation.

Contributor Activation Management

• Follow up with inactive contributors and track engagement
• Encourage participation and task completion

Documentation Management

Create and maintain style guides, FAQs, quality notes, calibration tasks, examples, trackers, honeypots, and onboarding materials.

Onboarding & Training

• Conduct onboarding sessions for trainers and reviewers
• Explain project workflows, quality standards, evaluation rubrics, JavaScript review requirements, testing expectations, and security considerations

Risk & Security Review

Identify unsafe code, security vulnerabilities, injection risks, authentication issues, unsafe dependency usage, data handling concerns, and production-readiness issues.

Process Improvement

• Identify recurring quality gaps and recommend workflow improvements
• Help build scalable QA processes for JavaScript AI training projects

Required Skills & Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, Information Technology, or related field — or equivalent professional experience
• 3+ years of experience in JavaScript development, frontend or backend engineering, Node.js, full-stack development, code review, or technical mentoring
• Strong understanding of closures, scope, hoisting, prototypes, Promises, async/await, event loop, modules, DOM APIs, error handling, data structures, and modern ECMAScript
• Ability to evaluate code for correctness, maintainability, readability, security, and rubric compliance
• Strong technical writing and documentation skills

Preferred Qualifications

• Experience with Node.js, React, Vue, Express, Jest, Mocha, Playwright, ESLint, Prettier, Vite, Webpack, or Babel
• Experience leading QA teams, review teams, engineering teams, or annotation teams
• Experience with AI training, LLM evaluation, prompt evaluation, code content QA, or rubric-based review
• Familiarity with Discord, GitHub, Google Docs, Google Sheets, and project management tools

Additional Information

• Fully remote work
• Flexible schedule
• Weekly payments
• Access to future opportunities through the SME Careers expert network

About SME Careers

SME Careers is an AI data services company and subsidiary of SuperAnnotate that provides training data for many of the world's leading AI companies and foundation-model laboratories.