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Synacktiv
Permanent (CDI) Full-time Senior Security AI Hybrid 5 Rue de la Baume, 75008 Paris, France · Hybrid EUR 55k-80k/year 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 5 Rue de la Baume, 75008 Paris, France · Hybrid
Compensation EUR 55k-80k/year Benefits & perks Budget recherche sécu, conférences, mutuelle. How to apply Présente un agent dev sécurisé avec audit trail complet.
Listed Jul 14, 2026
Updated Aug 3, 2026 Synacktiv is hiring a Senior Développeur IA agentique orienté sécurité Dev on the Security AI 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.
Synacktiv cherche un développeur IA orienté sécurité pour renforcer les pratiques secure-by-design sur agents et LLM.
Objectif : concilier vitesse de delivery et exigences d'auditabilité, contrôle et conformité.
Ce que vous allez faire
Livrer en production des agents IA sécurisés et auditables avec évaluation offline, monitoring et plan de rollback. Travailler avec produit, métier et design pour cadrer les besoins et priorités. Améliorer qualité des données, observabilité et KPI business liés aux usages IA. Documenter runbooks, incidents et standards de sécurité pour l'équipe. Profil recherché
Expérience concrète Python / stack ML-LLM avec features déjà déployées. Bonne pratique SQL, expérimentation et communication claire aux non-tech. Capacité à gérer les compromis qualité, coût, latence et sécurité. 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.
MLOps
Practical MLOps experience applied to LLM features, retrieval, agents, and evaluation in production or rigorous pilots.
Kubernetes Tool
Deploying and scaling model services with health checks, autoscaling, and rollout discipline.
Docker Tool
Containerized services and reproducible dev environments for ML and LLM workloads.
✓ You can show evidence in your application: Présente un agent dev sécurisé avec audit trail complet. ✓ Several of these show up in recent shipped work—not only on your CV: Python, LangChain, MLOps, Kubernetes, and Docker. ✓ 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-80k/year, benefits in At a glance) and your expectations align. What the employer asked for
Présente un agent dev sécurisé avec audit trail complet.
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