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Lavendo
San Francisco, California, United States; Toronto, Canada
Source: Lavendo careers · View original posting
From Lavendo's posting. “We” and “our” refer to the employer.
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.
Our client builds the data layer that AI agents run on. One API call turns any URL into clean, structured, LLM-ready data. It is already the default way a huge number of developers pull web data into their AI systems.
The numbers back it up: 8 figures in ARR in year one, more than doubled that in year two, and 180,000+ GitHub stars, placing its open-source project among the top 50 repositories of all time. They just closed a $75M Series B. The company is small, moving fast, and hiring people who want to build the next chapter with them.
The Mission
They believe developers and AI agents should not have to fight the web to get useful data out of it. Every hour spent maintaining a scraper, dealing with stale pages, or working around brittle retrieval systems is an hour taken away from the actual product.
Their job is to make that problem disappear: give AI systems reliable access to the live web, then make the results clean, current, structured, and useful enough to power real products.
The Opportunity
As a Search Engineer, you will own ranking quality and relevance for an LLM-driven search and retrieval product.
This is a role for an engineer whose primary, hands-on discipline is production search quality. You have personally shipped ranking or re-ranking changes, measured their impact, and can clearly describe the relevance, recall, conversion, or other search-quality metric you improved—including the result.
You will work directly with the Head of Search and a small team across crawling, indexing, retrieval, and search serving. These systems are central to delivering excellent results at scale, but they are not substitutes for relevance ownership. Your role is to improve search quality while navigating the real constraints of web-scale retrieval: freshness, deduplication, latency, reliability, and cost per query.
Compensation
San Francisco: $235,000–$260,000 USD base salary, plus competitive equity.
Toronto: $217,000–$233,000 CAD base salary, plus competitive equity.
8 figures in ARR in year one, more than doubled in year two. 180,000+ GitHub stars and a developer base showing up before you even start selling to them. $75M Series B closed in 2026, backed by top-tier investors
~40 people total, real visibility with the founders and leadership. No layers, no committees, fast decisions, short feedback loops
We are proud to be an equal opportunity workplace and consider all qualified applicants without regard to race, color, religion, national origin, age, sex, marital status, ancestry, disability, genetic information, veteran or military status, gender identity or expression, sexual orientation, or any other characteristic protected by law.
LAYIQ is an independent job-discovery service. This listing does not imply a partnership with or endorsement by the employer. Review the original posting for current details and availability.
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