{"id":4240824,"url":"https://alion.io/job/mantra-ai-engineer","title":"AI Engineer","company":{"id":3991199,"name":"Mantra","domain":"mantra.io","url":"https://alion.io/company/mantra-io","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"freelance","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["France"],"countries":["FR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon ECS","optional":false},{"name":"Amazon Kinesis","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"DynamoDB","optional":false},{"name":"Embeddings","optional":false},{"name":"FastAPI","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Git","optional":false},{"name":"GitLab","optional":false},{"name":"Jira","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Next.js","optional":false},{"name":"Poetry","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"TypeScript","optional":false},{"name":"JavaScript","optional":true},{"name":"React.js","optional":true}],"status":"live","first_seen_at":"2026-11-13T10:29:58Z","employer_posted_date":null,"last_verified_at":"2026-11-13T10:29:58Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"Au sein de l’AI Factory du groupe, l’équipe AI Platform construit et opère la plateforme agentique du groupe : le socle unique sur lequel sont créés, déployés et exploités les agents IA. L’équipe maintient ce socle et l’enrichit en continu : catalogue d’agents, connecteurs MCP, catalogue de skills, interfaces conversationnelles et intégrations aux systèmes du groupe.\n\nLa plateforme sert deux familles d’utilisateurs :\nLes équipes techniques de l’AI Factory (AI engineers et data scientists d’AI Products et de Business Science), qui construisent les produits IA du groupe ;\n\nLes tandems AI Builder / métier, qui créent des agents et des RAG pour les fonctions RH, marketing, finance ou éditoriales.\n\nDescription de la fonction :\nEn tant qu’AI Engineer, vous construisez et industrialisez les briques de ce socle, et vous accompagnez les équipes qui les utilisent.\n\nConstruction de la plateforme :\nDévelopper et faire évoluer les briques du socle agentique : orchestration d’agents, connecteurs MCP, skills, mémoire, gestion des prompts, garde-fous.\n\nConcevoir et industrialiser des agents : configuration des prompts, des tools, des connexions MCP et des guardrails.\n\nConcevoir et industrialiser les chaînes de RAG : ingestion, découpage, indexation, recherche, évaluation de la pertinence.\n\nIntégrer la plateforme aux sources de données et aux systèmes du groupe, notamment Snowflake et les APIs internes.\n\nIndustrialisation & Mise en production :\nDéployer les services sur AWS, avec conteneurisation, infrastructure as code et pipelines d’intégration et de déploiement continus.\n\nMettre en place l’observabilité : logs, traces, métriques, alertes, suivi de la qualité des réponses.\n\nConstruire les jeux d’évaluation et les tests automatisés des agents, pour mesurer les régressions avant chaque livraison.\n\nAssurer le run : traiter les incidents, améliorer la performance et la fiabilité, réduire la latence et les coûts.\n\nAccompagnement des utilisateurs de la plateforme :\nAider les équipes AI Products et Business Science à porter leurs produits sur la plateforme.\n\nAppuyer les AI Builders sur les sujets techniques, et rendre les briques du socle réutilisables et documentées.\n\nContribuer aux revues de code et aux choix d’architecture de l’équipe.\n\nProfil recherché\nExpérience :\n4 ans d’expérience minimum en ingénierie logicielle, dont une expérience réelle de mise en production d’applications à base de LLM.\n\nExpérience de projets cloud et d’architectures microservices.\n\nCapacité à travailler sur un socle partagé, avec des exigences de qualité, de sécurité et de maintenabilité.\n\nCompétences Techniques (indispensables) :\nLangages : Python.\n\nFrameworks : FastAPI, LangGraph / LangChain ou équivalent.\n\nCloud AWS : Bedrock, ECS, S3, DynamoDB.\n\nData : Snowflake, SQL.\n\nIA générative : RAG, agents ReAct, MCP, recherche sémantique et embeddings.\n\nArchitecture : conception d’API REST, microservices, OAuth2 et OIDC, injection de dépendances.\n\nObservabilité : tracing distribué, logs structurés.\n\nOutils : Docker, Poetry, Git, CI/CD GitLab.\n\nCompétences Techniques (appréciées) :\nLangages : TypeScript.\n\nFrameworks : Next.js.\n\nCloud AWS : Lambda, Step Functions, Kinesis, AWS Batch.\n\nData : bases vectorielles.\n\nIA générative : workflows agentiques, fine-tuning ou hébergement de modèles.\n\nOutils : Jira.\n\nLangues : Français et anglais courants (équipes réparties sur plusieurs pays).\n\nAtouts (Les Plus) :\nExpérience d’une plateforme interne mutualisée entre plusieurs équipes.\n\nExpérience dans les médias, la télévision ou le streaming.\n\nSensibilité aux enjeux de sécurité, de confidentialité et de conformité des données.\n\nQualités Personnelles :\nAutonomie et goût du travail en équipe.\nCapacité à expliquer simplement un choix 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Docs: https://alion.io/developers"}}