Real Estate Data & Intelligence Engineer

Build has created the agentic AI stack for institutional real estate, automating complex development and acquisitions workflows. This role owns turning fragmented real estate data sources into a single, trusted picture of every site and asset, and building the intelligence that sits on top of it. You will work alongside the geospatial team and domain experts to decide which sources matter, connect and cross-reference them, catch inconsistencies and hidden assumptions, and turn the results into answers the AI and clients can act on.

Responsibilities

The real estate data layer: ingesting, cleaning, linking and cross-referencing property, land, power, planning and market data sources into one record per site and asset; Entity resolution and data quality: matching parcels, owners, titles and addresses across sources, and flagging conflicts and gaps before they reach a decision; The intelligence on top: comps selection, valuation and NOI inputs, distress and pricing-gap signals, and risk and red-flag detection that AI workflows and experts use; New sources: finding, evaluating and onboarding data that makes site validation faster and more accurate; The speed, reliability and coverage of all of the above as Build expands into new markets

Requirements

Data engineer or data scientist background at a real estate data company who has stitched together property records at scale; engineer on a research, analytics or data team at a brokerage, investor or advisory firm who wants to build rather than report; geospatial or ML engineer who has built valuation or site selection models on messy real-world data; typically a CS, data engineering or similarly technical background; a few years of experience; real curiosity about how the built world gets valued and built

Benefits

Radical autonomy and real ownership; meaningful, generous equity; accelerated founder's track; elite teammates; perpetual adventure with extraordinary experiences and shared meals; opportunity to shape the built world