About the role
About us
Complir is the AI platform for the product compliance lifecycle, built for retailers, brands, and manufacturers selling physical consumer products across multiple markets.
We believe getting a physical product to market shouldn't mean fighting spreadsheets, PDFs, and supplier emails just to prove it's safe and legal to sell. Product compliance should be continuous, automatic, and understandable, not a bottleneck that slows launches down. We're building the AI infrastructure that makes that possible.
We work with many of the world's largest retailers and brands across fashion, furniture, cosmetics, toys, electronics and many other product categories. We're backed by Y Combinator, and a roster of investors who see what we see: Product compliance is the next major infrastructure category, and we're leading it.
About the role
Every product you've ever bought, from a kid's toy dinosaur to your electric toothbrush, had to clear a wall of regulation before it reached you. That wall is written down somewhere: scattered across hundreds of government portals, PDFs, and legal databases, in dozens of languages, updated on no schedule anyone agreed to.
Your job is to turn that chaos into structured, queryable data our product can act on. You'll be the person who makes the world's product regulations machine-readable.
The data layer everything stands on
This is not a role where you write Python scripts in isolation. You'll understand, crawl, and monitor regulatory sources across hundreds of jurisdictions, parse raw legal text into a normalized requirement schema, and catch changes the day they land, so every label, Declaration of Conformity, and risk assessment we generate is provably current.
The interesting problems are everywhere: government portals that were last redesigned when fax machines were current, legal text that means different things in different translations, amendments that quietly rewrite three other acts, and the question of how you prove to an enterprise customer that your data was correct on the day they shipped. LLMs make structured extraction over legal text possible for the first time; making it reliable enough to stake a product launch on is the engineering problem you'll own.
