About us
We’re third-time founders (MasterClass, Outlier.org, etc.) building a new way to apply AI to the education system.

Education is a trillion-dollar market that hasn’t meaningfully innovated in 150 years. Costs rise. Outcomes fall. Students everywhere deserve better.

Our mission
Fix education and help every student on earth reach their full potential.

Our plan

1. Build an AI Teacher Assistant/Grader that saves teachers 10-15 hours a week by automating assessment and reporting, while producing the most accurate, real-time student performance data in the world.

2. Sell access to that data layer to schools and parents.

3. Expand into adjacent products (personalized learning, predictive interventions, competency-based certifications) all powered by the same core data.

What we believe

• You can only improve what you measure.

• Every student deserves the chance to express their unique gifts.

• The best results come from personalized instruction.

• The AI platform shift is the biggest opportunity of our lifetimes to improve education.

You are

• An ambitious, product-minded, AI-native software engineer.

• A builder, not a researcher.

• Comfortable using LLMs daily in your workflow.

• Excited to use AI to make the world better.

• 2+ years into your career as a production engineer.

• Strong with RAG/retrieval, embeddings, evaluation loops.

• Experienced building (if not architecting) large-scale data systems.

• Ready to work in-person with the team in NYC.

You will

• Ship end-to-end: features across TypeScript/React and a Python/Go backend.

• Build with LLMs: prompting, evals, guardrails, RAG.

• Fine-tune models (or leverage tuned ones) to optimize accuracy, latency, and cost.

• Design and operate pipelines to ingest classroom artifacts at scale.

• Work side-by-side with founders, shaping MVP → V1 and early technical choices.

How we work

• Small, senior-leaning team (hiring 1–3 founding engineers now).

• Weekly sprints, fast iterations, regular contact with users.