Frontend Engineer, Document Intelligence
HebbiaNew York City; San Francisco, CA$160k – $300kPosted 7 April 2026
Tech Stack
Job Description
About Hebbia
The AI platform for investors and bankers that generates alpha and drives upside.
Founded in 2020 by George Sivulka and backed by Peter Thiel and Andreessen Horowitz, Hebbia powers investment decisions for BlackRock , KKR , Carlyle , Centerview , and 40% of the world’s largest asset managers. Our flagship product, Matrix, delivers industry-leading accuracy, speed, and transparency in AI-driven analysis. It is trusted to help manage over $30 trillion in assets globally.
We deliver the intelligence that gives finance professionals a definitive edge. Our AI uncovers signals no human could see, surfaces hidden opportunities, and accelerates decisions with unmatched speed and conviction. We do not just streamline workflows. We transform how capital is deployed, how risk is managed, and how value is created across markets.
Hebbia is not a tool. Hebbia is the competitive advantage that drives performance, alpha, and market leadership.
The Team
The Document Intelligence team at Hebbia builds cutting-edge AI solutions that transform how users discover and interact with billions of private and public documents. Our products, including the Hebbia’s Browse application, enable intelligent document exploration, powerful search capabilities, and deep insights extraction. We focus on developing advanced data ingestion and search technologies that deliver intuitive, explainable, and highly responsive experiences. Working closely with customers, our team continuously iterates to address real-world challenges and drive impactful, data-driven decisions. Our goal is to empower users by seamlessly turning vast and complex document repositories into actionable intelligence.
The Role
As a Frontend Software Engineer on the Document Intelligence team, you will play a crucial role in designing, developing, and delivering intuitive and interactive user interfaces tailored specifically for Hebbia's document-first AI applications, such as our Browse platform, enabling intelligent document discovery across private data. Your key challenge will be crafting user interfaces that provide explainability, steerability, and interruptibility, essential for effectively engaging with sophisticated, agentic AI systems. You will lead major frontend features from conceptualization through deployment, closely collaborating with cross-functional teams of engineers, AI experts, and designers to architect scalable solutions, build robust interactive experiences, and ensure seamless reliability and performance. Your technical creativity, user-centered design thinking, and exceptional problem-solving skills will directly shape the usability, effectiveness, and innovation of Hebbia’s AI-driven document discovery applications.
Responsibilities
Be an owner . We are a small and growing team relying on each and every engineer to provide significant coverage.
Build without prior art. Agentic interfaces do not have templates or pre-existing guidelines to rinse and repeat - you will be setting the standard for an industry.
Own critical system components. Take complex requirements and turn them into robust, scaled solutions that solve real customer needs.
Unlock meaningful customer value. Our customers aren’t using Hebbia for the gimmick - they unlock market moving value. You will be responsible for unlocking this Alpha.
Who You Are
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field. A strong academic background with coursework in data structures, algorithms, and software development is preferred.
5+ years software development experience at a venture-backed startup or top technology firm.
Proficiency in React, Typescript, and popular frontend frameworks for component design and state management.
Deep expertise in one or multiple: full-stack development, frontend engineering, web development, UX/UI engineering.
Knowledge of cloud platforms and application deployment platforms (e.g., AWS, Vercel)
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