## Company Overview
**Rhizome AI**
Rhizome AI (YC W26) is building Glean for life sciences. We will universally organize and make accessible the world's life science information for agents so they can help us 10x the number of therapies coming to market.
Chetan (our CEO)’s last role was building an AI inference platform for drug discovery at a company with 140m raised. He saw the incredibly things that were becoming possible to come up with drug candidates, but it was clear that the bottlenecks were only getting more severe on the path for these candidates to come to market.
We've started this journey by indexing and powering retrieval across >3 TB of public regulatory and clinical data. Rhizome Ask - our regulatory agent - is helping dozens of companies understand exactly what the FDA or EMA expects. This is critical to prepare for regulator meetings, write documentation, and automate compliance activities. ChatGPT and Claude do poorly in these scenarios, they just don't have the right harness and tools.
We’re a remote team of 4 with 6 figures in ARR, climbing rapidly.
## The Role
As a Founding Full Stack AI Engineer you'll work across the entire stack - from OCR ingestion to retrieval to the agent layer to the UI - to improve the product and expand what it can do. Your work directly helps companies doing lifesaving work for patients.
We're deployed on DigitalOcean, using Next.js, TypeScript, FastAPI, Python, Postgres, ParadeDB, Tailwind, Clerk, Logfire, PostHog, and Checkly for testing. Our agent is built on both Anthropic and OpenAI's models.
We heavily leverage AI to write code. Production still needs to be extremely reliable, our customers do critical work after all. But it's critical to achieving our ambition that we lean into what has recently become possible.
## What you'll work on
1. Helping our AI Regulatory Affairs coworker do more - editing docx / pptx, monitoring alerts, reviewing documents, etc.
2. Scaling our >55 data infrastructure pipelines. We expect >125 by EOY and >500 by end of 2027.
3. Immersing yourself into the domain - learning the difference between small molecules and biologics. Understanding the life cycle of a drug's path to market. Understanding what the different phases of clinical trials are for.
4. Improving the accuracy and throughput of our OCR-ing, indexing, retrieval, and citation framework
5. Improve our regulatory agent and build similar, more specialized agents to automate end-to-end activities
6. Engaging directly with customers, if that interests you
## Requirements
1. Hand-write <10% of the code that you ship to prod.
2. 6+ years of relevant software engineering experience
3. Strong full-stack experience - comfortable owning a feature from database to UI
4. Experience with search/retrieval, RAG, or LLM-backed products is a strong plus
5. Experience as a scientist, data scientist, or being an applied ML engineer is a strong plus
6. High-ownership mindset and the ability to work independently
7. 5 hours of daily overlap with Pacific Time (GMT-8)
8. Fully remote, with willingness to travel for a 1-week offsite every 2–3 months
9. Have been directly responsible for production systems in the past
10. Worked for <50 person, VC-backed American teams in the past
## How we work
1. Async, written-first communication with minimal meetings
2. Ship fast, iterate
3. High autonomy and trust
Keywords: healthcare, pharma, biotech, medical device