Product Engineer
Rowspace - San Francisco, California, United States, New York City
Posted Feb 4, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Product Engineer San Francisco, California, United States, New York City The Role Full Stack Engineers at Rowspace are at the heart of building our product. You'll shape the platform from the ground up. In a typical week, you might build a pipeline that turns 50-page investment memos into searchable knowledge in seconds, design a UI that helps analysts trace AI answers back to source documents, or ship a custom agent workflow based on feedback you heard from a customer that morning. What You'll Do - Design and build intuitive user interfaces that become deeply embedded in investors' daily workflows - Build APIs that allow Rowspace to work seamlessly across chat tools, custom workflows, and external applications-such as ChatGPT, Claude, and Excel - Build ingestion pipelines that turn messy, scattered data, such as PDFs, emails, spreadsheets, structured data, into a unified knowledge engine that underlies all of our products - You'll talk directly to customers, hear their pain points firsthand, and ship solutions within days - You will be responsible for maintaining the highest standards of security, privacy, and system reliability as you work with sensitive investment data - You will build comprehensive eval sets to ensure the reliability of our LLM systems Who You Are - You've shipped full-stack products before (React/Typescript + Python/Node or similar) - You've designed data models and APIs at scale and enjoy the challenge of getting the schema right - You're excited about productionizing AI, not just using LLMs, but building reliable products to deliver
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