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JavaScript Developer

AgileGrid Solutions

full-remotemidpermanentfullstack United States 45 days ago via LinkedIn

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Tags

JavaScriptReactNode.jsVue.jsGitCode ReviewDebuggingAI IntegrationDocumentationRemote Work

About the role

Role overview

You will join a remote team as a JavaScript Developer. The role focuses on improving the quality of AI-generated code and building reliable JavaScript solutions that support Labelbox’s AI data annotation platform.

Responsibilities

  • Review AI-generated code to find errors, inconsistencies, and improvement opportunities while maintaining strong quality standards.
  • Develop and implement robust JavaScript solutions to improve functionality and performance of the platform.
  • Collaborate with data scientists, AI researchers, and developers to integrate new features and optimize existing ones.
  • Participate in code reviews, pair programming, and team meetings to support best practices.
  • Maintain and update documentation for code changes, system architecture, and development processes.
  • Stay current with industry trends and emerging technologies in JavaScript and AI integration.
  • Troubleshoot and resolve technical issues quickly to minimize downtime and maintain stability.

Requirements

  • Bachelor’s degree in Computer Science, Software Engineering, or related field.
  • 3–5 years of professional JavaScript development experience.
  • Proficiency with modern JavaScript frameworks such as React, Node.js, or Vue.js.
  • Experience reviewing and debugging AI-generated code.
  • Strong understanding of software development best practices and Git.
  • Excellent problem-solving and attention to detail.
  • Ability to work independently and collaboratively in a remote environment.
  • Good communication skills for cross-functional collaboration.

Nice to have / additional context

  • Experience working on AI/data annotation integrations and improving platform reliability.

About AgileGrid Solutions

Labelbox is an AI research and data platform company focused on helping organizations develop, manage, and deploy machine learning models. Its core work centers on data annotation, data management, and quality assurance, enabling AI teams to accelerate development and improve model accuracy.

Scraped 4/1/2026

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