# What forward deployed engineering means

> Engineers inside your team, measured on a system in production, not on hours or slides.

Published 2026-11-12 by Entelech. https://blog.entelech.ai/forward-deployed-engineering/

"Forward deployed engineer" is a job title that is showing up everywhere in AI. It is worth being precise about what it means, because it changes who is accountable when the system goes live.

## Inside, not alongside

A forward deployed engineer works inside your organisation: in your cloud, in your repository, on your data, next to the people who do the work today. Not in a separate lab that sends over a prototype. Not in a slide deck.

That matters because most of what makes an AI system work is local knowledge. Which fields in the ERP are actually filled in. Which exceptions the team handles by phone. Where the real decision happens. You only learn that by sitting in the work.

## Measured on production

Consultants are usually measured on hours or deliverables. A forward deployed engineer is measured on one thing: a system running in production that beats the baseline.

So the questions change. Not "is the model clever enough?" but "does this reduce the error rate on real invoices?" Not "did we hit the milestone?" but "is someone on your team now able to run this without us?"

## Your data stays where it is

Because the work happens in your environment, your data goes nowhere new. We configure model providers so your data is not used for training, and we log decisions and model versions so risk teams and EU AI Act reviews have something concrete to look at.

## You own everything at the end

Code, prompts, evals, pipelines and documentation: all of it belongs to you. A forward deployed engagement is designed to end with your team running the system, not with a dependency on ours.

## Model-agnostic by design

We work with whichever model fits the task and your policies. Entelech is part of the Anthropic Partner Network and the OpenAI Partner Network, and we also deploy open and cloud-provider models. The engineering, the evals and the ownership stay the same whichever model sits underneath.

## The short version

Forward deployed means we come to the work, build the system where it will run, prove it against today's numbers, and hand you the keys.