About the role
structured by ORIProduct: AI-Native Real Estate Intelligence Platform Stage: Seed / Idea Stage Ukrainian is a plus Location: Remote (Europe) 🚀 The Opportunity We’re building the intelligence layer for the real estate market . Our platform automatically discovers, normalizes, and analyzes property data from thousands of unstructured,…
What you will do
- Design and build a scalable data ingestion system for messy, anti-bot-protected sources.
- Create a centralized data / knowledge layer that normalizes and connects property information across sources.
- Develop an analytics & ML layer to compute market signals and detect anomalies.
- Use LLMs as an interface and reasoning layer on top of structured data and computed metrics.
- Work directly with the founders on product decisions and technical direction.
What they are looking for
- Strong experience building production systems from scratch .
- Solid backend, frontend and data engineering background (language-agnostic).
- Comfort working with unstructured data and unstable sources .
- Practical understanding of ML / analytics pipelines (not research-heavy).
- Experience using LLMs in real systems (beyond simple API calls).
- Ownership mindset and interest in early-stage, high-impact work.
Nice to have
- Ukrainian is a plus
- Experience as a founding or early-stage engineer .
- Knowledge graphs or complex data models.
- Work in PropTech, FinTech, or market intelligence products.
Before you apply
- Share your GitHub, portfolio, or examples of systems you’ve built involving data pipelines, analytics, or AI-driven products.
Full posting text
Product: AI-Native Real Estate Intelligence Platform
Stage: Seed / Idea Stage
Ukrainian is a plus
Location: Remote (Europe)
🚀 The Opportunity
We’re building the intelligence layer for the real estate market .
Our platform automatically discovers, normalizes, and analyzes property data from thousands of unstructured, real-world web sources .
The goal is not listings or document search - but structured market intelligence : trends, anomalies, and investment-relevant signals.
As our first engineering hire , you’ll design the core architecture from 0→1 , build the data and intelligence foundation, and grow into a technical leader as the team scales.
🧠 What You’ll Own
Design and build a scalable data ingestion system for messy, anti-bot-protected sources.
Create a centralized data / knowledge layer that normalizes and connects property information across sources.
Develop an analytics & ML layer to compute market signals and detect anomalies.
Use LLMs as an interface and reasoning layer on top of structured data and computed metrics.
Work directly with the founders on product decisions and technical direction.
Establish engineering standards and help scale the team over time.
What Matters Most (Core Requirements)
Strong experience building production systems from scratch .
Solid backend, frontend and data engineering background (language-agnostic).
Comfort working with unstructured data and unstable sources .
Practical understanding of ML / analytics pipelines (not research-heavy).
Experience using LLMs in real systems (beyond simple API calls).
Ownership mindset and interest in early-stage, high-impact work.
Current Technical Direction (Flexible)
This reflects our current direction , not a strict checklist.
We care more about how you think than whether you’ve used every tool.
Backend: Node.js
Data: PostgreSQL (+ optional graph or vector extensions)
Ingestion: Playwright / similar scraping approaches
Analytics & AI: ML for signals and anomaly detection
LLMs: agentic workflows, tool-using LLMs, optional MCP
Frontend: Angular/React
Infra: Cloud (AWS/GCP), Docker, CI/CD
⭐ Nice to Have
Experience as a founding or early-stage engineer .
Knowledge graphs or complex data models.
Work in PropTech, FinTech, or market intelligence products.
Important Note
We don’t expect one person to permanently cover every layer.
Your initial focus will match your strengths, and we’ll hire around you as the product grows.
How to Apply
Share your GitHub, portfolio, or examples of systems you’ve built involving data pipelines, analytics, or AI-driven products .
Originally posted on Himalayas