{"id":2024282,"url":"https://alion.io/job/smart-point-tech-lead-data-retrieval-ia-generative-rag-fh","title":"Tech lead Data & Retrieval – IA Générative / RAG F/H","company":{"id":2390068,"name":"Smart 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sein d’une équipe spécialisée en Data et Intelligence Artificielle, vous intervenez sur des problématiques à forte dimension technique autour de la gestion de données, de l’Information Retrieval et de l’IA générative.\nVotre mission consiste à concevoir et industrialiser les pipelines permettant de collecter, transformer, indexer et rechercher de grands volumes de données, afin d’alimenter des applications basées sur les LLM et les architectures RAG.\nVous serez également impliqué dans les choix d’architecture, l’amélioration de la pertinence des recherches et l’industrialisation des solutions en production.\n\nVos principales missions\nData Engineering & Indexation\nConcevoir et industrialiser des pipelines d’ingestion de données provenant de sources hétérogènes.\n\nMettre en œuvre les traitements de parsing, nettoyage, normalisation et chunking.\n\nConcevoir et maintenir des systèmes d’indexation à grande échelle.\n\nMettre en œuvre des bases vectorielles et des embeddings.\n\nGarantir la qualité, la fraîcheur, la traçabilité et la scalabilité des données et des index.\n\nRetrieval & RAG\nConcevoir des stratégies de recherche sémantique et hybride.\n\nCombiner recherche lexicale (BM25), embeddings, filtrage et reranking.\n\nMettre en place des indicateurs de pertinence : Recall, Precision, nDCG, MRR.\n\nOptimiser les mécanismes de Retrieval alimentant les LLM et architectures RAG.\n\nTravailler sur la gestion du contexte, la déduplication et la qualité des résultats.\n\nArchitecture & qualité\nParticiper aux choix techniques et à l’évolution de la stack Data/IA.\n\nMettre en place les bonnes pratiques de développement : Clean Code, SOLID, tests automatisés.\n\nAssurer l’observabilité des pipelines et des services.\n\nContribuer à la sécurité et à la conformité des données.\n\nAccompagner techniquement les équipes et partager les bonnes pratiques.\n\nEnvironnement technique\n\nIndispensable :\nPython 3.11+\n\nData Engineering / Information Retrieval\n\nEmbeddings / NLP\n\nRecherche sémantique et hybride\n\nRAG / LLM\n\nBases vectorielles : Qdrant, Weaviate, pgvector, OpenSearch\n\nPostgreSQL\n\nTests avec Pytest\n\nEnvironnement apprécié :\nLangChain\n\nOpenAI, Mistral, Amazon Bedrock\n\nBM25 / reranking\n\nKafka\n\nRedis\n\nAirflow / Spark\n\nDocker / Kubernetes\n\nCI/CD\n\nGo ou Java\n\nProfil recherché\nDe formation supérieure en informatique, Data, IA ou domaine équivalent, vous disposez d’une expérience significative en Data Engineering, Information Retrieval ou IA appliquée, idéalement sur des environnements à forte volumétrie.\nVous maîtrisez notamment :\nla conception de pipelines Data industrialisés ;\n\nl’indexation et la recherche sur de grands volumes de données ;\n\nles embeddings et la recherche vectorielle ;\n\nles architectures de Retrieval et RAG ;\n\nl’évaluation et l’optimisation de la pertinence des résultats ;\n\nles problématiques de qualité, traçabilité et versioning des données.\n\nVous êtes à l’aise dans les environnements techniques complexes et souhaitez participer à des projets au croisement de la Data Engineering et de l’IA générative.\nUn bon niveau d’anglais est requis pour évoluer dans un contexte international.","description_format":"text","description_chars":3113,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-07T13:04:23Z"}],"visa":[],"liveness":{"score":11,"band":"cold","label":"Long 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