AI-Driven Full-Stack Engineer — End-to-End Platform

LearnVector Inc.

Mountain View (CA)

On-site

USD 180,000 - 240,000

Full time

14 days+

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Job summary

LearnVector Inc. in Mountain View, CA is hiring an engineering leader to build our AI-powered learning platform end to end. You will shape the architecture early and own major components spanning frontend, backend, data, and deployment, delivering scalable AI-driven experiences.

You will ship daily alongside a small, fast-moving team including Andrew Ng, focusing on observability, testing, and reliable system design in a high-growth environment.

Qualifications

  • AI-native approach in day-to-day work.
  • 4+ years building and shipping production web applications end to end.
  • Strong TypeScript/JavaScript skills and modern web frameworks (React/Next.js).
  • Solid backend engineering (Node or Python) and API design.
  • Experience integrating LLM APIs into products and streaming experiences.
  • Ability to make architecture calls under uncertainty and explain reasoning.

Responsibilities

  • Build the product end to end: frontend, backend, data layer, and deployment.
  • Make foundational architecture decisions and revisit them as needed.
  • Build serving layer for AI-driven experiences with streaming responses and memory state.
  • Set engineering standards: testing, CI, observability, and safe trade-offs.
  • Ship daily alongside a founding team, including Andrew Ng, with direct exposure to product decisions.

Skills

AI-native
Production web apps
TypeScript/JS
Backend engineering
LLM APIs
Architectural judgment

Tools

React/Next.js
Node
Python
SQL

Job description

LearnVector Inc. in Mountain View, CA is hiring an engineering leader to build our AI-powered learning platform end to end. You will shape the architecture early and own major components spanning frontend, backend, data, and deployment, delivering scalable AI-driven experiences.

You will ship daily alongside a small, fast-moving team including Andrew Ng, focusing on observability, testing, and reliable system design in a high-growth environment.

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