Product Engineer — AI Infrastructure / Devtools

Lavendo partners with startups and high‑growth companies to help them hire top‑tier sales, GTM, and technical talent. This role is with one of our clients; we’ll share full details about the company and interview process as we get to know you and confirm mutual fit. About the Company Our client builds the data layer that AI agents actually run on. One API call turns any URL into clean, LLM-ready markdown or structured data — the boring-hard problem every team building with AI eventually slams into, solved for good. They hit eight figures in ARR in year one, then more than doubled it. 150,000+ GitHub stars and climbing, driven entirely by word of mouth — no paid acquisition, no growth hacks. Over 1.25 million developers and 150,000+ companies build on this platform today. They just closed a Series A led by a top-tier VC firm, with their existing accelerator and a well-known tech CEO angel investor also in the round. The team is roughly 35 to 39 people. Small on purpose. Hybrid in San Francisco, working shoulder to shoulder with the founder. The Mission Every AI lab, every agent, every model needs clean web data, and that demand isn't slowing down. This team is building the infrastructure that superintelligence will lean on to read and act on the web. You'd be getting in while the category is still being drawn, on a problem that gets more central to AI every single month. The Opportunity As a Product Engineer, you'll build the thing developers reach for when they need to turn the messy, hostile, constantly-shifting web into clean data and reliable actions an AI can take. This is real product engineering on the company's browser-automation and agent-interaction surface. You ship it, you own it, and it's in front of thousands of developers within days.

What You'll Do