AI-Driven Fullstack Engineer — React + Python

MACHINE LEARNING TECHNOLOGIES LLC; Sunnyvale (CA); On-site; USD 83,000 - 131,000; Full time

Job summary

MACHINE LEARNING TECHNOLOGIES LLC in Sunnyvale, CA seeks a skilled Full-Stack Engineer to build production-grade web apps and AI-powered agents. You will design the frontend in React, implement the backend in Python, and integrate LangChain/LangGraph for intelligent workflows.

Responsibilities include creating scalable APIs, embedding-based RAG solutions, and seamless LLM integration with tools. A strong emphasis on code quality, testing, and collaboration is required.

Qualifications

• Strong experience in React (hooks, components, state).
• Solid understanding of full-stack architecture, REST APIs and backend.
• Hands-on with LangChain for LLM app development.
• Hands-on with LangGraph for AI agent orchestration.
• Experience integrating LLM APIs (OpenAI, Anthropic, etc.).
• Knowledge of embeddings, vector databases and RAG architectures.
• Proficient with Git, version control and collaborative workflows.

Responsibilities

• Design, develop, and maintain full‑stack web apps using React frontend and Python backend.
• Build scalable, secure, production‑ready APIs and services.
• Implement AI agents and workflows with LangChain and LangGraph.
• Integrate LLMs, tool-calling, memory and multi‑step reasoning features.
• Design RAG solutions using embeddings and vector databases.
• Orchestrate agent state, control flow and execution with LangGraph.
• Ensure code quality through testing, reviews and best practices.

Skills

React

Python

REST APIs

LangChain

LangGraph

LLM APIs

RAG & embeddings

Git

Tools

Git

Job description

MACHINE LEARNING TECHNOLOGIES LLC in Sunnyvale, CA seeks a skilled Full-Stack Engineer to build production-grade web apps and AI-powered agents. You will design the frontend in React, implement the backend in Python, and integrate LangChain/LangGraph for intelligent workflows.

Responsibilities include creating scalable APIs, embedding-based RAG solutions, and seamless LLM integration with tools. A strong emphasis on code quality, testing, and collaboration is required.