AI role · Open offer

AI Agent Engineer — tools & workflows

Mistral AI

Permanent (CDI)
Full-time
Senior
Applied agents
Hybrid
Paris, Île-de-France, France · Hybrid
Paris, France
EUR 75k–105k/year + BSPCE

This listing is optimized for AI-native talent: clear skills and tools so candidates know if they fit before they apply—and so you spend less time screening mismatches.

4 skills2 tools

At a glance

How you'll work, where, and key listing dates.

Employment: Permanent (CDI), Full-time
Workplace: Hybrid
Location: Paris, Île-de-France, France · Hybrid
Compensation: EUR 75k–105k/year + BSPCE
Experience level: Senior
Team: Applied agents
Benefits & perks

About this role

What the team is looking for and how this position fits.

Mistral AI is hiring a Senior AI Agent Engineer — tools & workflows on the Applied agents team (Hybrid · Paris, France). This is a hands-on role in LLM & generative AI—not a generic “AI enthusiast” post.

You will own LLM features, retrieval, agents, and evaluation end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.

Mistral AI builds European frontier models and enterprise platforms from Paris.

AI Agent Engineer: tool-calling agents, workflows, and evals on Mistral models (FR/EN).

Missions

Concevoir des agents avec outils, mémoire et garde-fous production.
Mettre en place des evals de réussite de tâche et de coût.

Stack & environment

Python, LangChain, PyTorch, Docker, Kubernetes.

What we look for

Agents ou copilots en prod; français et anglais; autorisation de travail FR.

Skills we're hiring for

What each capability means for this role—not a keyword checklist.

Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
LangChain
Orchestrating LLM chains, tools, and retrieval with observable steps and failure handling.
PyTorch

Tools & stack

Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).

KubernetesTool
Deploying and scaling model services with health checks, autoscaling, and rollout discipline.
DockerTool
Containerized services and reproducible dev environments for ML and LLM workloads.

You're a strong fit if…

Tailored to this listing—use it as a self-check before you apply.

You can show evidence in your application: Agent with tools, memory, and eval harness (FR/EN).
Several of these show up in recent shipped work—not only on your CV: Python, LangChain, PyTorch, NLP, and Kubernetes.
You have owned LLM features, retrieval, agents, and evaluation in production: debugging live issues, running postmortems, and iterating from real user or business signals.
You are comfortable with the hybrid rhythm (Hybrid · Paris, France)—onsite collaboration when it matters, deep work when remote.
You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.
You read the full listing (comp: EUR 75k–105k/year + BSPCE, benefits in At a glance) and your expectations align.

Apply

Candidate accounts only: add your headline and bio on , and optionally a CV link or PDF so recruiters see your full résumé. Then write a short pitch below—applications use your login email.

What the employer asked for

Agent with tools, memory, and eval harness (FR/EN).

Register, add a headline and bio, then you can attach a CV link or PDF on My account before you apply. That keeps applications tied to your profile and makes it easier for employers to review your background.

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