AI Product Engineer

Understand Tech; Frontignan; On-site; EUR 60,000 - 90,000; Full time

Job summary

Understand Tech Inc. is expanding its AI platform with on-site deployments in Frontignan, France. We seek an AI engineer who codes, ships and talks to customers, owning scope from roadmap to support.

You will build and operate AI components, run inference on NVIDIA GPUs, and ensure governance and GDPR compliance for enterprise clients. You will own the data architecture, prototype with RAG pipelines, and deliver demos with sales.

Qualifications

• 3+ years of experience in machine learning or AI engineering.
• At least one LLM project shipped to production.
• You show ownership, autonomy and urgency.
• Strong Python, FastAPI and Git skills.
• You know how to build a RAG pipeline end-to-end.

Responsibilities

• Build the platform's AI components: RAG, embeddings, document ingestion pipelines, prompts and agent chains, answer evaluation.
• Run and optimize LLM inference on NVIDIA GPUs: deploy and tune inference engines (vLLM, TensorRT-LLM, NIM, Ollama), quantization, batching, KV cache, throughput and latency on single machines and multi-GPU racks.
• Operate models in production on customer hardware: model lifecycle, versioning, monitoring, GPU usage, upgrades without downtime.
• Work on the data architecture: vector stores, migration to pgvector, model selection (Nemotron, Qwen, gpt-oss, etc.) and benchmarking.
• Own your product: roadmap, trade-offs, GitHub ticket prioritization, sign-off on what goes to production.
• Handle technical support for a few accounts: reproduce a bug reported on Slack, find the root cause, fix it or get it fixed, reply to the customer.
• Build demos and POCs for prospects with the sales team.
• Write the documentation for what you ship, for the team and for customers.

Skills

Python

FastAPI

Git

LLM deployment

GPU optimization

Multilingual communication

Tools

NVIDIA GPUs

vLLM

TensorRT-LLM

Ollama

PostgreSQL

MongoDB

Firebase

Docker

Kubernetes

AWS

GCP

pgvector

Job description

We're looking for an AI engineer who codes, ships and talks to customers. You own your scope, from roadmap to support, and you work directly with demanding enterprise customers in France and abroad.

Understand Tech is a startup of around ten people building an AI platform for enterprises: assistants, agents, business apps, and NVIDIA servers delivered to the customer's site (AI-in-a-Box) for those who want to keep their data in-house. Our customers come to us for sovereignty, GDPR compliance and AI governance. We work with Dell and NVIDIA, and we serve international customers across industries, from semiconductors to professional services.

We're now expanding to help our customers build their own AI factories: on-premises infrastructure, platform and applications, all running in their walls. That's where this role comes in: the models you serve, and how fast and reliably they run on the customer's hardware, are a big part of what we deliver. We're growing fast, which makes for a stimulating environment: things move all the time, we adapt constantly, and there's real room to grow.

What you'll do

• Build the platform's AI components: RAG, embeddings, document ingestion pipelines, prompts and agent chains, answer evaluation.
• Run and optimize LLM inference on NVIDIA GPUs: deploy and tune inference engines (vLLM, TensorRT-LLM, NIM, Ollama), quantization, batching, KV cache, throughput and latency on single machines and multi-GPU racks.
• Operate models in production on customer hardware: model lifecycle, versioning, monitoring, GPU usage, upgrades without downtime.
• Work on the data architecture: vector stores, migration to pgvector, model selection (Nemotron, Qwen, gpt-oss, etc.) and benchmarking.
• Own your product: roadmap, trade-offs, GitHub ticket prioritization, sign-off on what goes to production. Current example: our TCG (Test Case Generator), which generates test cases from technical specs.
• Handle technical support for a few accounts: reproduce a bug reported on Slack, find the root cause, fix it or get it fixed, reply to the customer.
• Build demos and POCs for prospects with the sales team.
• Write the documentation for what you ship, for the team and for customers.

Your profile

You have 3+ years of experience in machine learning or AI engineering, including at least one LLM project shipped to production.

• You show ownership, autonomy and a sense of urgency.
• Solid Python, FastAPI or equivalent, Git every day.
• You've built a RAG pipeline end to end: chunking, embeddings, vector database, evaluation.
• You've served LLMs yourself on NVIDIA GPUs with vLLM or an equivalent engine, and you know how to make them faster: quantization, batching, context length, memory.
• You know PostgreSQL and at least one NoSQL database (MongoDB, Firebase).
• Docker without pain. Linux, CUDA drivers and GPU troubleshooting don't scare you. Kubernetes, AWS or GCP are a plus.
• You can explain a technical problem to a non-developer customer, in French and in English (a good share of our customers write in English).
• You go all in. On your scope, you decide what we build and you're accountable for it; you don't just code tickets. And you like being challenged on your decisions.

Nice to have: software testing or test generation, fine-tuning (LoRA, etc.), experience with Blackwell or Grace Blackwell hardware.

Details

Contract: Permanent (CDI)

Location: Frontignan

Salary: To be discussed

Start date: As soon as possible

Process: A conversation with key leaders, a hands-on case study, a meeting with the tech team