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Salary
$140k per year
Location
Hybrid (France)
Seniority
Senior · 7+ years exp
Employment
Freelance

First seen by Alion on Sep 2, 2026.

Overview
Company
Impact
Profile match
Beezen is a French company working on sustainability reporting under standards such as CSRD, GRI, SASB and TCFD, and it states a commitment to ISO 27001 information security. It hires Python, DevOps, data and MLOps engineers and product owners for cloud and data platform projects. The company is headquartered in Puteaux, France.

nous recherchons un AI Engineer Python pour renforcer une équipe dédiée aux agents IA. La mission porte sur un agent conversationnel d'analyse de données déjà déployé en production : il s'agit d'en assurer la continuité, la robustesse et la montée en qualité. Équipe de 5 à 8 personnes (AI Engineers, Lead, PM, Manager), environnement 100 % GCP.

Vos missions :

- Faire évoluer et industrialiser la couche d'évaluation « LLM as a judge » : métriques de qualité des réponses, jeux de test, seuils, suivi et documentation
- Assurer la maintenance corrective et évolutive de l'agent en production (fiabilité, correction d'anomalies, mise à jour des composants)
- Mener des analyses LLM avancées pour comprendre le comportement de l'agent, identifier les axes d'amélioration et fiabiliser les résultats
- Intégrer le protocole A2UI pour la création et l'exposition de graphiques dans l'interface de l'agent
- Concevoir des workflows multi-agents (protocoles A2A / A2UI)

Profil recherché

- 4 à 7 ans d'expérience en AI Engineering Python
- Formation Bac+5 (école d'ingénieur ou université) en informatique, ou expérience équivalente
- Must have : conception de workflows multi-agents et protocoles A2A/A2UI ; maîtrise de GCP (Vertex AI / Agent Engine, Cloud Run, Cloud Batch, Pub/Sub, Cloud Logging, Cloud Tracing) ; parsing et structuration de données non structurées (PDF, images, tableaux)
- Nice to have : ADK, LangChain, LangGraph, LlamaIndex, FastAPI, Pydantic, Pandas, NumPy, MCP, bases vectorielles (embeddings, indexation, requêtage), recherche hybride et re-ranking, pipelines QA / LLM-as-a-Judge, sécurisation des systèmes IA (anti prompt injection, filtrage PII/RGPD), optimisation des coûts IA (tokens, cache sémantique, choix des modèles)
- Français courant à l'écrit et à l'oral : échanges réguliers avec le métier

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