About Reducto

Reducto is the agentic document platform for leading AI teams who demand enterprise performance at scale. We provide a comprehensive toolkit for working with documents the way a human would, combining custom in-house and leading frontier models to power efficient and accurate document workflows.

We’ve grown rapidly, increasing revenue 8x year over year and partnering with hundreds of companies, from leading AI teams like Harvey, Vanta, and Scale, to enterprise customers across FAANG and top trading firms.

Reducto has raised over $100M from world-class investors including a16z, Benchmark, and First Round Capital.

The Opportunity

As a Backend/AI Engineer, you'll work on our core API that powers document parsing for hundreds of companies. You'll integrate cutting-edge LLMs, optimize document processing pipelines, and build the infrastructure that makes state-of-the-art document understanding accessible at scale.

We would love to meet you if you

Philosophy: You are your own worst critic. You have a high bar for quality and don't rest until the job is done right—no settling for 90%. We want someone who ships fast, with high agency, and who doesn't just voice problems but actively jumps in to fix them.

Experience: You have 2+ years of experience building real world applications and integrating LLMs into production systems

Language: You're exceptional at Python

Tools: Build your own tools as needed—like a quick Streamlit app to test hypotheses or create a dataset.

Approach: A quantitative approach to building products. Ability to debug, experiment, and iterate fast. You should be comfortable getting hands-on with the full development lifecycle, from ideation to shipping to users.

The core work will include

Integrating and optimizing LLM calls for structured extraction, form filling, and document understanding tasks

Making improvements to API design and pre-processing algorithms (chunking, structured extraction, etc.) based on customer feedback

Building and improving document processing pipelines that handle everything from PDFs to spreadsheets at scale

Experimenting with new techniques and output structures to improve LLM accuracy and reduce latency

Building internal tooling and evals to better understand/analyze failure cases

Working directly with the founders and customers to shape the product direction and engineering strategy

Bonus points if you

Have prior experience founding a company or building products at early stages

Have experience with prompt engineering, fine-tuning, or building AI agents

Are ambitious and driven, and care a lot about doing great work with great people

Keep up with the latest developments in ML/AI

This is an in person role at our office in SF. We're an early stage company which means that the role requires working hard and moving quickly. Please only apply if that excites you.

About Reducto

Nearly 80% of enterprise data is in unstructured formats like PDFs

PDFs are the status quo for enterprise knowledge in nearly every industry. Insurance claims, financial statements, invoices, and health records are all stored in a structure that’s simply impractical for use in digital workflows. This isn’t an inconvenience—it’s a critical bottleneck that leads to dozens of wasted hours every week.

Traditional approaches fail at reliably extracting information in complex PDFs

OCR and even more sophisticated ML approaches work for simple text documents but are unreliable for anything more complex. Text from different columns are jumbled together, figures are ignored, and tables are a nightmare to get right. Overcoming this usually requires a large engineering effort dedicated to building specialized pipelines for every document type you work with.

Reducto breaks document layouts into subsections and then contextually parses each depending on the type of content. This is made possible by a combination of vision models, LLMs, and a suite of heuristics we built over time. Put simply, we can help you:

Accurately extract text and tables even with nonstandard layouts