Forward Deployed Engineer

TL;DR

We are seeking an entrepreneurial and driven individual with a keen interest in early-stage startups and consulting experience in Data Science, particularly with projects involving Knowledge Graphs and Large Language Models (LLMs).

Why this role exists

Every large enterprise we talk to has the same problem: their Gen

AI pilots hallucinate on their own data, and nobody trusts the output enough to put it in production. We solve this by combining LLMs with knowledge graphs, and it works. Large Defense, Banks and Manufacturers are already in production with us.

Now we need someone to sit on the customer's side of the table and make sure every deployment becomes a reference. Not a Customer Success Manager with a technical vocabulary but an engineer who writes code in the customer's repo, designs the ontology with their domain experts, and ships the integration that makes graph-based agents part of how the company actually works.

You'll be one of the second Forward Deployed Engineer at Lettria and help write the playbook for this function.

Why Lettria

The big labs are hiring FDEs in Paris too. Here's what's different here:

You'll be employee ~20, not ~2,000. What you learn on a deployment changes the product the following sprint. You'll talk to the founders daily.

The technical bet is sharper. Generic RAG is a commodity. Agents grounded in structured knowledge is where regulated industries actually trust Gen

AI. You'll go deep on graph modeling, ontology design, and graph-native retrieval, not just prompt engineering.

Customers are decision-makers, not pilots. Our buyers are Heads of Data, CDOs, and Chief Innovation Officers signing real contracts. You won't run lighthouse demos that go nowhere.

Trust is the product. Our entire wedge is making Gen

AI explainable and auditable enough for nuclear engineers or investment