Who we are

YaizY is an educational platform that helps schoolchildren master 21st-century skills and prepare for the digital professions of the future. We create courses in programming, animation, game design, multimedia, and other in-demand areas.

We operate in the US market, offer over 30 courses in 8 career tracks, and collaborate with 100+ schools in 18 states. Over 25,000 students have used our products.

We are now launching a new product from scratch for a new market – AI Math Tutor. This is a personal AI math tutor for schoolchildren that adapts to the student's level, identifies knowledge gaps, and guides them through explanations, practice, and verification to achieve confident mastery of the subject. We are creating a product capable of replacing a traditional math tutor.

What you will do

You will be one of the key developers of the new AI product – from architecture to production.

AI Math Tutor is a browser-based web application with a workspace (problem + whiteboard + AI chat) where the student solves problems, and the AI tutor analyzes the solution in real-time, diagnoses errors, and streams pedagogical feedback. Details:

• Designing and implementing server-side logic for integration with OpenAI (in the future, it may be another LLM)

• Fullstack development of the product: Vue 3 / Nuxt (frontend), Node.js / Fastify (backend), PostgreSQL, Redis

• Real-time interaction (WebSocket for streaming AI responses)

• AI response validation

Tech Stack

• Frontend: Vue 3 + Nuxt

• Backend: Node.js + Fastify, WebSocket (Socket.io)

• DB: PostgreSQL, Redis

• Infrastructure: Docker, GitLab CI

The tech stack may be adjusted. If you have arguments for a different solution, we are open to suggestions.

Requirements

• Full-time, remote work

• Proficient fullstack: Vue/Nuxt + Node.js — you can build a product from the database to the interface

• Practical experience integrating LLMs into a product (OpenAI API, Anthropic, or similar): prompting, streaming, structured outputs, error handling

• Understanding how LLMs work at a level sufficient for making architectural decisions: context window, tokens, temperature, function calling

• PostgreSQL, Redis, WebSocket — at a working level

• Principles of good architecture (SOLID, KISS, DRY)

Will be a decisive advantage

• Experience building AI features in production: RAG, agent scenarios, file search, AI response validation

• Experience with OpenAI Assistants / Responses API

We offer

• High salary in USD ($3,000-$4,000) and an employee stock option program

• Remote work with a flexible schedule

• Opportunity to build an AI product from scratch and make architectural decisions

• A dynamic team of experienced professionals, complete absence of bureaucracy

• Diverse and interesting tasks

• Rapid professional growth at the intersection of fullstack and AI