Founding Forward Deployed Engineer

Deploying and maintaining on-prem and VPC instances of Reducto’s systems, often with complex enterprise constraints (e.g. air-gapped, custom auth, strict latency targets).

Building tooling to make deployments faster, more reliable, and easier to debug.

Creating diagnostics, dashboards, and eval harnesses to measure performance and track regressions across environments.

Writing crisp internal documentation and playbooks for repeatable deployments.

Collaborating closely with customers, support, and core engineers to identify high-impact improvements.

Acting as a feedback loop to the product and infra teams—surfacing usability gaps, unmet needs, and opportunities to deepen customer value.

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

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

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.

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

Automatically convert graphs to tabular data and summarize images in documents

Extract important fields from complex forms with simple, natural language instructions

Build powerful retrieval pipelines using Reducto’s document metadata

Intelligently chunk information using the document’s layout data