Forward Deployed Engineer

We are looking for a Forward Deployed Engineer with 3–6 years of experience to sit at the intersection of deep engineering and customer impact — owning the technical deployment of Reducto's document AI platform with some of the world's most sophisticated enterprise customers. This is a founding FDE role at a 80-person, Series B company backed by a16z, Benchmark, and First Round Capital that's processing tens of millions of pages a month and growing revenue 8x YoY — you'll help shape what this function looks like from the ground up.

What will you be doing?

Partner with AEs and SEs during pre-sales to run rigorous evals, build custom demo applications, and win competitive bake-offs against rival document AI solutions.

Own post-sales technical success for 1–3 enterprise accounts — meeting weekly or bi-weekly with customers to unblock issues, deepen adoption, and unlock expansion into new use cases and teams.

Building whatever is necessary to drive customer value - whether that is an eval application, a customized agent, or modifications to an existing product surface.

Building close relationships with our customers and knowing the key stakeholders, particularly technical ones.

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

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

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

Key Requirements

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.

You have 3 to 6 years of experience deploying software in production settings—ideally with enterprise or regulated customers.

You're excellent with Python and can navigate Bash and infrastructure as needed.

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.

Bonus points if you:

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

Have prior experience in a forward-deployed type role, enabling large customer(s) to succeed through your efforts.

Keep up with the latest developments in ML/AI.