Constructor is the next-generation platform for search and discovery in e-commerce, built to explicitly optimize for metrics like revenue, conversion rate, and profit. Our search engine is entirely invented in-house utilizing transformers and generative LLMs, and we use its core and personalization capabilities to power everything from search itself to recommendations to shopping agents. Engineering is by far our largest department, and we've built our proprietary engine to be the best on the market, having never lost an A/B test to a competitive technology. We're passionate about maintaining this and work on the bleeding edge of AI to do so.
Out of necessity, our engine is built for extreme scale and powers over 1 billion queries every day across 150 languages and roughly 100 countries. It is used by some of the biggest e-commerce companies in the world like Sephora, Under Armour, and Petco.
We're a passionate team who love solving problems and want to make our customers' and coworkers' lives better. We value empathy, openness, curiosity, continuous improvement, and are excited by metrics that matter. We believe that empowering everyone in a company to do what they do best can lead to great things.
Constructor is a U.S. based company that has been in the market since 2019. It was founded by Eli Finkelshteyn and Dan McCormick who still lead the company today.
As a Product Designer on Searchandising within our Merchant Experience chapter, you'll design the end-to-end systems that let merchandisers fine-tune ranking and recall across Search and Browse shopping experiences. Your work won't be "nice-to-have UI"—it will directly influence net revenue, add-to-cart rate, RPV, and customer retention for some of the world's largest retailers.
You'll partner with PMs, engineers, data scientists, and merchandisers to transform complex, high-leverage workflows into intuitive tools: creating rule builders that feel effortless, visualizing ranking impact and conflicts in real time, and automating the tedious work of promotions so teams can move at the speed of retail. You'll bring transparency to cause-and-effect—showing how every change affects items, positions, and page metrics—while unlocking rapid experimentation with personalisation and AI-assisted suggestions.