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Salary
$175k – $200k per year
Location
In office (San Francisco)
Seniority
Middle · 3+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Sep 26, 2026. First seen by Alion on Sep 25, 2026.

Overview
Company
Impact
Profile match
Bloomy delivers personalized learning for K-12. Mastery-based progression, AI tutoring, and real-time dashboards.

About Bloomy

Bloomy is an AI tutor and curriculum for K-12 students. Our student users are learning approximately 2x faster in early pilots, and students and teachers alike love our product.

How it works: We diagnose students’ skill gaps, map out a personalized learning path for them, and then have an AI tutor teach them. The AI learns about how they learn, so it can increase the efficiency of its teaching and, consequently, their learning.

How you can help: You will be joining as the founding engineer. Right now, engineering is one founder (me) orchestrating fleets of coding agents that produce a large share of our code and curriculum against specs, verification harnesses, and QA gates. I’m a solo founder with domain expertise as a former teacher and sales leader, but I’m not an engineer by training, and I need someone with true technical expertise to actualize the vision of improving education for millions of students.

Why we’re different: Bloomy is AI-native. I built the entire product from February to April of this year, got it into the hands of 500 students across 6 schools from April to June, started YC in June, and have roughly doubled ARR every 2 weeks since then. Thousands of students will soon use our product this fall. Bloomy is also the first EdTech company to go through YC for the past 5 batches, so it represents an opportunity to be on the ground floor of one of relatively few startups trying to transform education with AI.

Your first 90 days

First week

Ship a feature or a fix to production and watch real students in real classrooms hit it the next school day. Our loop from “merged” to “a 6th grader used it” is as short as it gets.

First month

Get acquainted with the React/TypeScript app, the Supabase backend, the content pipeline, and the agent fleets that feed it. Take ownership of your first fleet - write the spec, build the harness, set the QA gate - and start shipping through it.

Three months later

Design the roadmap with me: ~50% shipping product across the stack, ~25% building and running agent infrastructure, ~25% talking to teachers, students, and districts - and turning what you hear into the roadmap.

Things we badly want to build

  • The data flywheel. Almost nobody in education closes the loop between that telemetry and the instruction itself. We can - for every answer, retry, AI-tutor conversation, and any other interaction - in days, not textbook-revision cycles. Design that loop.
  • Agent orchestration as a first-class engineering problem. Better harnesses, better evals, better verification - so that a dozen concurrent agents produce work you'd trust in front of a classroom.
  • Whatever schools need next. Today it's tools for students and teachers. The surface area in a school district is enormous, and you'll help decide where we go.

We're looking for someone who

  • Has 5+ years shipping products that real end users touch daily, and has opinions about what makes them good
  • Is high-agency: can take ambiguous feedback and turn it into shipped product without waiting for a spec
  • Is expert-level with AI coding tools and uses them to move dramatically faster - without outsourcing judgment to them
  • Gets excited, not exhausted, by the idea of managing a dozen concurrent agents
  • Wants tight feedback loops with real users (some of whom are eleven)
  • Has high schlep tolerance - roster CSV imports, school-device performance quirks, and school-specific customization are part of the job and part of why we win
  • Cares about measurable learning outcomes, not just engagement metrics

Preferred experience

  • TypeScript, React, Postgres (we're React 18, Vite, Tailwind, shadcn/ui, Supabase, TanStack Query, on Vercel)
  • LLMs in production: agents, evals, tool use, context management
  • Building codebases and pipelines designed to be worked on by agents
  • Event telemetry, analytics, or experimentation systems
  • Edtech background genuinely not required

The backstory

I started my career as a 7th grade English teacher, where I saw how hard teaching 30 different kids at 30 different levels of understanding really is. After building the driver acquisition engine at Lyft, pursuing various entrepreneurial ventures while getting my MBA at Stanford, and building AI agents and workflows at McKinsey from the start of the boom, I now believe education is where AI can have the largest positive impact for society.

Compensation

- $175K - $200K

- 1.5 - 2.0% equity

Founding-engineer package - meaningful ownership from day one.

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