Product Engineer — Search

Firecrawl Inc.

Job Overview

Location

San Francisco, CA (Hybrid) OR Remote (Americas, UTC-3 to UTC-10)

Job Type

Full-time

Full Job Description

📋 Description

• As a Product Engineer — Search at Firecrawl Inc., you will be the critical bridge between cutting-edge search research and tangible developer-facing product improvements, ensuring that advancements in retrieval and ranking are not just technically sound but also delightfully usable by developers who rely on the platform for LLM-ready data extraction.
• You will own the end-to-end experience of Firecrawl’s search API — from conceptualizing improvements based on research insights to implementing API changes, updating documentation, refining error handling, optimizing latency, and ensuring every touchpoint feels intuitive and reliable for developers building on the platform.
• You will actively dogfood the search API by building internal tools and side projects with it, rigorously testing new features before release, and continuously monitoring GitHub issues, Discord threads, and support tickets to identify friction points and opportunities for improvement before users report them.
• You will collaborate closely with Search/IR and RL Research Engineers to translate complex technical work into product decisions — evaluating what to expose to users, what to abstract away, and how to balance technical elegance with practical usability, ensuring that shipped features solve real developer problems.
• You will run rapid product experiments: forming hypotheses about search improvements, instrumenting changes, shipping them quickly, measuring impact on developer experience and performance, and iterating based on data — even when imperfect — to maintain a high velocity of innovation.
• You will champion developer experience (DX) as a first-class concern, obsessing over API consistency, response structure, error messaging, latency, and documentation accuracy, knowing that these details determine whether developers feel frustrated or delighted when using Firecrawl.
• You will work within a small, high-impact team of 26 people where your contributions directly shape the product’s direction and usability, operating in a culture of urgency, ownership, and technical excellence where shipping fast and learning faster is the norm.
• You will grow into a rare hybrid engineer who deeply understands both the intricacies of search infrastructure (ranking, retrieval, vector databases, APIs) and the nuances of product design for technical users — becoming someone who can not only build robust systems but also anticipate how developers will interact with them, making you uniquely valuable in AI-driven infrastructure.

🎯 Requirements

• 3+ years of experience in applied reinforcement learning, machine learning engineering, or model training with a proven track record of deploying models into production systems.
• Strong background in building or improving search or discovery features, particularly in developer-tools environments, with hands-on experience using technologies like Elasticsearch, Vespa, or vector databases.
• Demonstrated ability to own features end-to-end — from design and implementation to deployment, monitoring, and iteration — with a bias toward shipping and learning quickly in ambiguous environments.

🏖️ Benefits

• Competitive salary range of $180,000–$290,000/year, adjusted fairly for location outside the U.S. based on cost of living.
• Equity grant of up to 0.15% in Firecrawl, allowing you to own a meaningful stake in the company’s growth.
• Comprehensive benefits package including 100% employer-paid medical, dental, and vision for U.S.-based employees, 12 weeks fully paid parental leave, $100/month wellness stipend, $1,000/year learning and development stipend, and 3-month paid sabbatical after 4 years of service.

Skills & Technologies

Elasticsearch

GitHub

Remote

$180k-290k

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Firecrawl Inc.

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About Firecrawl Inc.

Firecrawl Inc. provides an API that converts entire websites into clean markdown or structured data. Designed for AI applications, the service crawls all accessible subpages, renders dynamic content, and returns LLM-ready output without requiring sitemaps. It includes built-in scraping, search, and extraction capabilities for building knowledge bases, fine-tuning datasets, or powering chatbots. The company targets developers and data teams who need reliable web content ingestion at scale, offering cloud-hosted endpoints and self-hosted options under a usage-based pricing model.

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