Senior Founding Software Engineer
10 hours ago
TL;DR — We're looking for world-class founding software engineers to help build the world's first AI-native university — where every student learns with their own private AI professor — no teachers, no lectures.
About Masterschool
Masterschool is an applied education research lab on a mission to unlock human potential. We're building the school of the future: an AI-native institution that's an order of magnitude more effective than traditional education.
This school won't just solve the Two Sigma Problem and deliver a truly personalized, world-class education—it will make that education accessible to everyone, regardless of background or circumstance.
We're a group of educators, researchers, and engineers building software and models at the edge of what's possible—with the goal of improving the lives of billions.
You can see our work in action here.
Founding engineer
As a founding engineer, you'll join the core team that builds the foundation of Maestro.
It's 0 1 work — fast, focused, and hands-on. You'll tackle deep technical challenges, design systems from first principles, and help push the limits of what's possible.
It's intense, but also deeply rewarding — the joy of building real things, from the ground up, with people who care about doing great work.
What you'll do
- Contribute to every stage of development — design, build, test, deploy, and improve.
- Own and deliver end-to-end features — from pixels on screen to database depth.
- Define, document, and uphold modern engineering best practices.
- Build state-of-the-art AI systems using LLMs, agents, and adaptive learning models.
- Write clean, maintainable, and testable code that others can build upon.
- Review code thoughtfully and help raise the team's technical bar.
Requirements:
- Seasoned builder: 5+ years as a full-stack or backend engineer, designing and scaling robust web and mobile applications.
- Architect-level thinker: Deep understanding of system design, clean architecture, OOP principles, and modern engineering best practices — from scalability and performance to maintainability and clarity.
- Proven ability to design and implement AI-centric user interactions: using LLMs, agents, and custom pipelines to build rich, adaptive experiences where systems reason, act, and collaborate seamlessly — huge plus.
- Deep understanding of modern AI engineering: from multi-agent orchestration and dynamic context retrieval to token efficiency, grounding external data, memory architectures, and real-time streaming of model outputs — big plus.
- Hands-on experience with our core stack: , React, , MongoDB, Redis, — plus.
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