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Product Engineer — Search

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: AI Chopping Block, Inc.
Full Time position
Listed on 2026-06-18
Job specializations:
  • Software Development
    Backend Developer, AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 180000 - 290000 USD Yearly USD 180000.00 290000.00 YEAR
Job Description & How to Apply Below

Product Engineer — Search

You’ll own the developer-facing search experience at Firecrawl — taking the retrieval and ranking improvements coming out of research and shipping them as a product developers can’t stop using. This isn’t a pure research role and it isn’t a pure backend role. You sit at the intersection: you understand how the systems work deeply enough to improve them, and you care about how they feel to use obsessively enough to make them great.

At a 26‑person company, the gap between research and shipped product is exactly one person. You’re that person.

Salary Range: $180,000–$290,000/year (Range shown is for U.S.

-based employees. Compensation outside the U.S. is adjusted fairly based on your country's cost of living. You can explore how we calculate this here: https://(Use the "Apply for this Job" box below).)

Equity Range: Up to 0.15%

Location: San Francisco, CA or Remote (Americas, UTC‑3 to UTC‑10)

Job Type: Full‑Time

Experience: 3+ years in applied RL, ML engineering, or model training — with production systems

Visa: US Citizenship/Visa required for SF; N/A for Remote

About Firecrawl

Firecrawl is the easiest way to extract data from the web. Developers use us to reliably convert URLs into LLM‑ready markdown or structured data with a single API call. In just a year, we’ve hit 8 figures in ARR and 100k+ Git Hub stars by building the fastest way for developers to get LLM‑ready data.

We’re a small, fast‑moving, technical team building essential infrastructure superintelligence will use to gather data on the web. We ship fast and deep.

What You’ll Do

Ship search improvements that developers notice. Take retrieval and ranking improvements from research and turn them into product changes that make developers say “this just works.” You know that a 200 ms latency improvement isn’t just a benchmark win — it’s a better product. You ship the whole thing: the API change, the docs update, the example that makes it obvious.

Own the search API end‑to‑end. You’re responsible for how Firecrawl’s search endpoint feels to integrate, use, and build on. That means response format, latency, error handling, pagination, filtering — every surface a developer touches. You’re the person who notices when something is confusing before a user files a Git Hub issue about it.

Dogfood relentlessly. You build things with the API before you ship them. You feel the friction before your users do. You read every Git Hub issue, every Discord thread, every support ticket that touches search — not because someone asked you to, but because that’s where the product signal lives.

Translate research into product decisions. You work closely with the Search/IR and RL Research Engineers. You understand their work well enough to make good product calls about what to prioritize, what to expose to users, and what to keep under the hood. You ask good questions. You push back when something technically elegant would make the API worse.

Run fast product experiments. You form a hypothesis about what would make search better for developers, instrument it, ship it, measure it, and decide quickly. You’re comfortable making calls with imperfect data because waiting for perfect data means shipping nothing.

Raise the bar on developer experience. Firecrawl’s users are technical. They have high standards. They notice when response formats are inconsistent, when error messages are unhelpful, when documentation doesn’t match behavior. You notice too — and you fix it before they have to ask.

What We’re Looking For

Obsessive about developer experience. You think about DX the way a designer thinks about pixels. Latency, response structure, error messages, API ergonomics—these things matter to you on a visceral level. You’ve built APIs that developers loved and you know the difference between an API that works and one that delights.

Speaks both product and engineering fluently. You can read a ranking algorithm and understand its implications for the search experience. You can write the API spec and implement it yourself. You don’t need a PM to tell you what matters or an ML engineer to explain why a retrieval change is significant. You connect those dots on your…

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