It's our AI workforce, running 24/7 for thousands of restaurants across Spain. None of it starts from clean data. Thousands of suppliers, no standards, documents that contradict each other, an entire industry's economics buried in paper and spreadsheets.

We're not adding a chatbot to an ERP. Someone who parallelizes hypotheses with coding agents, stays relentlessly focused on AI that scales and solves real customer pain, and measures before optimizing without ever letting analysis slow down shipping. haddock is the AI-powered back-office for restaurants. We started as a system of record (inventories, purchases, invoices, bank reconciliation, P&L; reports) and turned it into the harness where our AI workforce lives.

Our vision is to lead the market through innovation, strong relationships, and by becoming the go-to tech partner for restaurant success. haddock is backed by Y Combinator, the accelerator behind Airbnb and Twitch.

Our ambitions are growing: more customers, more AI automation, more product surface, more value. Our engineers don't wait for a project to be defined. They create momentum, propose ideas, and are a key part of the company's growth.

Every invoice and delivery note a restaurant receives goes through our OCR. Fina sits on top of everything haddock knows about a restaurant: purchases, suppliers, stock, sales, bank movements, P&L.; Ask it anything about the business and it answers, and increasingly it goes and does the work instead of just reporting on it.

It's the surface where the whole system has to behave as one, and most of what it will become is still unbuilt. Complex reconciliations, data workflows, and imports of the most chaotic data you can imagine: a supplier catalogue inside a photographed PDF,



a POS export nobody ever documented, ten years of a restaurant's history in a spreadsheet built by six different people. Turning the messy free text of thousands of suppliers into a clean catalogue a restaurant can run its inventory on.

They are ours, we maintain them, and the quality of every agent we ship depends on them. The tools it can call, the data it can read, the guardrails, the place where a human steps in: you build the backend, the frontend and the plumbing that turns a model into something thousands of restaurants rely on every day. Running the experiment, reading the numbers and deciding whether it's worth it is part of the job, not something you get to when there's time left over.

We'd rather find out first than read about it later. 2+ years of hands‐on experience with GenAI and 3+ years of engineering experience overall. One year of very intense AI work also counts, if it's backed by solid software or data science experience. ~ As a reference: an agent or workflow doing at least 5,000 executions a month, and you were the one accountable for it. You've worked with an eval system to measure and improve model performance, rather than a handful of test prompts and a good feeling. ~ You combine engineering rigor with product thinking.

Fluent in Spanish and comfortable in English. RAG systems and vector databases TypeScript, Python, langfuse, PostHog, Google Cloud Platform, mastra, Postgres, MongoDB, and several AI providers. First and foremost, the project itself: a fast-growing startup with ambition, product-market fit, and great culture A bright modern office in Barcelona, Poblenou, probably the best office you've ever worked at At least 2 days per week at the office (in-person collaboration) + 3 days WFH for focus

📌 PRODUCT ENGINEER (English) (Barcelona)
🏢 haddock
📍 Barcelona