Full-Stack MERN Developer with AI/LLM Integration

Posted 4 hours ago

Worldwide

Summary

We are looking for a skilled Full-Stack Developer proficient in the MERN stack (MongoDB, Express.js, React, Node.js) who also has hands-on experience integrating AI models and APIs into production web applications. ### ๐ŸŽฏ Key Responsibilities: - Build and maintain responsive UI components in React. - Design scalable backend APIs using Node.js & Express to communicate with LLMs (e.g., OpenAI, Anthropic Claude, or open-source models). - Set up efficient data storage & retrieval using MongoDB alongside Vector Databases (e.g., Pinecone, Qdrant, ChromaDB, or MongoDB Atlas Vector Search) for RAG applications. - Manage stream responses, rate limiting, and token optimizations for smooth UX. - Ensure clean, maintainable architecture and secure authentication. ### ๐Ÿ› ๏ธ Required Technical Skills: - MERN Stack: MongoDB, Express.js, React, Node.js (JavaScript/TypeScript) - AI & LLM Tools: OpenAI API, LangChain / LlamaIndex, Claude API, or custom AI pipelines - Databases: MongoDB + Vector Search / Pinecone / Weaviate - State & Async Handling: WebSockets, Server-Sent Events (SSE) for streaming text, RESTful APIs ### ๐Ÿ“‹ To Apply, Please Include: 1. Links to 1โ€“2 live projects or GitHub repos where you integrated AI with a full-stack JS web application. 2. What AI framework or vector database you prefer for RAG/chat implementations and why. 3. Your availability (hours/week) and time zone.

  • Less than 30 hrs/week
    Hourly
  • 1-3 months
    Duration
  • Intermediate
    Experience Level
  • $15.00

    -

    $35.00

    Hourly
  • Remote Job
  • Ongoing project
    Project Type
Skills and Expertise
Mandatory skills
JavaScript
MongoDB
API
Node.js
Activity on this job
  • Proposals:20 to 50
  • Interviewing:
    0
  • Invites sent:
    0
  • Unanswered invites:
    0
About the client
Member since Aug 16, 2025
  • PAK
    Lahore12:44 AM
  • $145 total spent
    3 hires, 0 active
  • 7 hours
  • Sales & Marketing
    Small company (2-9 people)

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