Founding Engineer

About HankYour home is your most valuable asset, and it runs on chaos. Home maintenance is opaque, reactive, and overwhelming, and the data that could fix it is locked inside one-time PDF inspection reports nobody ever opens again.Hank turns that data into something alive. We start at the home inspection (the one moment a professional documents every system in a house) and build a structured, normalized record of the home: every object, condition, and issue. Inspectors use Hank to do their job; that same data flows straight into a homeowner app where it becomes a living, AI-powered system for understanding and maintaining the home. Think "CarFax for homes," except it keeps working long after the sale.We're small, technical, and AI-first: a founder (previously built revenue systems at Stripe and LinkedIn) plus two senior engineers (from Cal.com and Housecall Pro). Pre-seed, shipping fast.The roleYou'll be the founding engineer for the homeowner experience: the consumer app and the AI and data systems behind it. This is a vertical to own, not a backlog to work through. The homeowner app already turns inspection data into a structured property dashboard (Objects, Issues, Initiatives, Quotes). Where it's going is much bigger:A team of specialized AI agents that help homeowners understand their home, prioritize maintenance, generate scopes of work, and compare contractor quotes.A relational, longitudinal property record that connects every system in the home and gets smarter with every inspection, sensor reading, and repair.Predictive maintenance, fair-price analysis, a private neighbor-trust network, and eventually a conversation that replaces the dashboard entirely ("What should I deal with this spring?").You'll make the architecture and product calls that define this side of the business, working directly with the founder and the engineering team.What you'll doDesign the homeowner data model: a normalized, relational, time-series record of a home (Postgres / Supabase).Build the applied-AI layer: multi-agent systems, retrieval over property data, and a "triggers before LLMs" approach that keeps cost and latency low (deterministic rules first, model calls only when reasoning is genuinely required).Ship full-stack product end to end (Next.js / React / TypeScript), from data layer to polished consumer UI.Build the pipelines that ingest and structure messy real-world data (inspection reports, property records, appliance manuals, sensor feeds).Treat privacy and consent as first-class: homeowners control their data, and the architecture has to enforce that.What we're looking forSenior engineer who has built and shipped products 0-to-1. You've owned things, not just closed tickets.Strong data modeling and relational database skills (Postgres). You think in entities, relationships, and how data ages.Hands-on applied AI / LLM experience: building with the major model APIs, agentic or multi-agent systems, RAG, and real judgment about when not to reach for an LLM.Full-stack fluency: TypeScript, React / Next.js, modern backend.Genuine product sense. You can make UX and scope calls and you care how the thing feels.Startup temperament: thrives in ambiguity, moves fast, low ego, high ownership.Bonus pointsProptech, home services, marketplaces, or fintech-grade trust/privacy experience.Built agentic AI systems or worked with an Agent SDK.Data engineering / ETL / scraping background.React Native (we have a mobile surface, with more coming).A real eye for design.Compensation and logisticsFounder-level equity and genuine ownership of a vertical.We're pre-seed and we'll be straight with you about exactly where things stand: cash compensation becomes market-competitive when our round closes.NYC / Connecticut area preferred so we can build together in person sometimes; fully remote is possible for the right person.Modern stack, AI-first culture, and a greenfield surface with enormous scope.How to applyApply here on LinkedIn, or email [careers@hihank.com] with something you've built that you're proud of.