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Contentsquare
Permanent (CDI) Full-time Mid GenAI product Hybrid 7 Rue de Madrid, Paris, IDF 75008, France · Hybrid Paris, France EUR 55k–75k/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.
Employment
Workplace Hybrid
Location 7 Rue de Madrid, Paris, IDF 75008, France · Hybrid
Compensation EUR 55k–75k/year + BSPCE Benefits & perks BSPCE, assistant analytics B2B, hybrid Paris 8e. How to apply Bibliothèque de prompts + métriques eval pour copilote analytics.
Listed Jul 31, 2026
Updated Aug 3, 2026 Contentsquare is hiring a Mid Prompt Engineer — analytics copilot on the GenAI product 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.
Contentsquare équipe plus de 1 000 marques avec analytics digitaux et un copilote IA pour insights produit.
Prompt Engineer (hybride Paris 8e) : concevoir prompts, jeux d'éval et métriques qualité pour assistant analytics B2B.
À propos de Contentsquare
Scale-up française leader experience analytics. GenAI intégré au cœur du produit pour insights automatiques. Bureaux Paris avec équipes produit et recherche. Missions
Maintenir bibliothèque prompts versionnée par use case. Définir golden sets et métriques hallucination/pertinence. Itérer avec PM et ingénieurs sur guardrails multilingues. Stack & environnement
Python, LangChain, OpenAI API, eval harness interne. Hybride Paris 8e ; anglais courant. Profil recherché
2+ ans prompt engineering ou LLM produit. Éligibilité travail en France. 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.
OpenAI API
Calling frontier APIs with retries, cost controls, prompt versioning, and safety filters.
NLP
Text pipelines: tokenization, fine-tuning, evaluation, and guardrails for user-facing language features.
✓ You can show evidence in your application: Bibliothèque de prompts + métriques eval pour copilote analytics. ✓ Several of these show up in recent shipped work—not only on your CV: Python, LangChain, OpenAI API, NLP, and Vector DBs. ✓ 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 55k–75k/year + BSPCE, benefits in At a glance) and your expectations align. What the employer asked for
Bibliothèque de prompts + métriques eval pour copilote analytics.
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Prompt Engineer — analytics copilot
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