JavaScript Team Lead

AI Trainer Jobs; United States; Remote; USD 58,000 - 96,000; Full time

Job summary

AI Trainer Jobs, a SME Careers subsidiary, seeks a JavaScript Quality Assurance Lead (QAL) to oversee quality and trainer performance across JS AI training projects. This remote hourly contractor role reviews AI-generated JS, provides precise feedback, and ensures alignment with project rubrics.

You will guide remote teams, maintain documentation, and help onboarding. Strong JS expertise and English communication are essential for success.

Qualifications

• Bachelor's or Master's degree in CS or related field, or equivalent experience.
• Excellent English communication to provide clear technical feedback in English.
• 3+ years of professional JavaScript development, frontend/backend, or related QA workflows.
• Strong knowledge of core JavaScript concepts and modern ECMAScript features.
• Ability to evaluate JS content against rubrics and identify issues.
• Familiarity with JS ecosystems and tools preferred.
• Experience leading or supporting remote teams is a plus.

Responsibilities

• Quality monitoring: spot-check JS items, provide ongoing feedback, and escalate as needed.
• Code review: evaluate AI-generated code, debugging responses, and explanations for correctness and clarity.
• Trainer/QA communication: update on Discord about guidelines, changes, and rubrics.
• Question handling: respond clearly to JS behavior, async logic, environments, and tooling.
• Activation management: DM inactive contributors, track follow-ups, and flag availability issues.
• Documentation: create and maintain JS project docs, style guides, FAQs, onboarding materials.
• Onboarding and training: run calls to explain expectations and requirements.
• Quality alignment: ensure consistent application of JS review guidelines across teams.
• Risk and security review: flag unsafe or misaligned code, injection risks, and data handling.
• Process improvement: identify gaps and help build scalable QA processes.

Skills

AI Training

JavaScript QA

Code Review

Debugging

Trainer Feedback

Test Coverage

Frontend Development

LLM Evaluation

Node.js

JavaScript

Education

Bachelor's or Master's degree

Tools

Node.js

npm/yarn/pnpm

React

Vue

Express

Jest

Mocha

Playwright

ESLint

Prettier

Vite

Webpack

Babel

DevTools

Job description

Pay: up to $70/hour

In this hourly, remote contractor role, you will work as a JavaScript Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across JavaScript AI training projects. You will review AI-generated JavaScript code and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards.

You will assess work for code correctness, reasoning quality, runtime behavior, debugging accuracy, readability, maintainability, performance, security awareness, test coverage, formatting, instruction-following, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong JavaScript expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote technical teams.

This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your JavaScript quality leadership will directly help improve the world’s premier AI models by ensuring that JavaScript training data is accurate, executable, logically sound, clearly explained, well-documented, and aligned with client expectations.

Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.

Important:

There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.

Responsibilities

• Quality monitoring: Spot-check JavaScript items, identify quality issues, provide ongoing feedback through DMs, and escal…
• Code review: Evaluate AI-generated JavaScript code, debugging responses, implementation explanations, algorithmic solutions, frontend/backend snippets, tests, and step‑step reasoning for correctness and clarity.
• Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and JavaScript‑specific review standards.
• Question handling: Respond to trainer/QA questions clearly and promptly, especially around JavaScript behavior, async logic, browser vs Node.js environments, frameworks, package usage, testing, edge cases, and rubric interpretation.
• Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow‑ups, and flag availability issues when needed.
• Documentation: Create and maintain JavaScript project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
• Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and JavaScript‑specific review requirements.
• Quality alignment: Ensure all trainers and QAs apply JavaScript review guidelines consistently and understand updates as projects evolve.
• Risk and security review: Flag unsafe, misleading, insecure, or overconfident code recommendations, especially around injection risks, dependency usage, authentication, browser security, data handling, and production readiness.
• Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for JavaScript AI training projects.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Technology, or a closely related field; equivalent professional software engineering experience may be considered.
• Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear technical feedback in English.
• 3+ years of professional experience in JavaScript development, frontend engineering, backend development with Node.js, full-stack engineering, code review, software QA, technical mentoring, or related workflows.
• Strong understanding of core JavaScript concepts such as closures, scope, hoisting, prototypes, promises, async/await, event loop, modules, DOM manipulation, error handling, data structures, and modern ECMAScript features.
• Ability to evaluate JavaScript content against detailed rubrics and identify issues such as incorrect logic, non-executable code, flawed reasoning, missing edge cases, poor async handling, security risks, performance problems, hallucinated APIs, or incomplete explanations.
• Familiarity with common JavaScript ecosystems and tools such as Node.js, npm/yarn/pnpm, React, Vue, Express, Jest, Mocha, Playwright, ESLint, Prettier, Vite, Webpack, Babel, or browser developer tools is preferred.
• Experience leading or supporting remote teams of trainers, annotators, reviewers, engineers, technical writers, coding mentors, or QAs is strongly preferred.
• Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, and project management systems.
• Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, calibration tasks, and other quality documentation.
• Experience with AI training, data annotation, large language models, prompt/response evaluation, code content QA, or rubric-based LLM evaluation is a strong plus.

Skills: AI Training, JavaScript, JavaScript QA, Debugging, Trainer Feedback, Test Coverage, Frontend Development, LLM evaluation, Code review, Node.js

Open to candidates in: The United States

Interview language: English