Senior RAG Engineer - LangChain/Production AI Systems

About UsWallester is a cutting-edge financial technology company that specializes in providing innovative solutions for businesses seeking to modernize their payment systems. By offering white-label card issuance platforms, seamless integration with existing infrastructure, and comprehensive support for both digital and physical cards, Wallester empowers companies to enhance their financial services and customer experience. Recognized as a leader in the FinTech space, Wallester has earned a reputation for its state-of-the-art technology, security, and scalability. Whether you are a startup or an established enterprise, Wallester delivers flexible, reliable solutions tailored to meet the evolving needs of the digital economy.About The RoleWe're seeking an exceptional engineer specialized in RAG (Retrieval-Augmented Generation) systems to build Wallester's intelligent knowledge base. You'll be responsible for the architecture, development, and deployment of a RAG system capable of ingesting housands of documents (Drive, emails, history) and providing perfect institutional memory accessible in natural language.Progressive deployment over 9 months: General knowledge base → Department integrations (Sales, Finance, Support) → Advanced features and scaling.We're looking for a true expert capable of designing and implementing complex RAG architectures with LangChain/LangGraph and orchestrating workflows with n8n.What You'll DoGeneral Knowledge BaseDesign complete RAG architecture with LangChainImplement Google Drive ingestion pipeline (5000+ documents)Build 3-way hybrid search (semantic + BM25 + pattern matching)Deploy Supabase with pgvector optimizationCreate LangGraph workflows for orchestrationDepartment IntegrationsConnect Pipedrive (Sales), Admin Panel (Finance), Support systemsDevelop autonomous agents per department with LangGraphBuild n8n workflows for business logicImplement conversation memory and query routingProduction & ScalingOptimize for 1000+ queries/day with <1s latencyImplement intelligent caching and error handlingSet up RAG evaluation metrics (precision, recall, faithfulness)Monitor with LangSmith/LangFuseWhat You'll NeedTruly masters LangChain/LangGraph in productionHas built production RAG systems (not just POCs)Understands trade-offs (latency, quality, cost, chunking)Knows the LangChain ecosystem (LangSmith, LangFuse, integrations)Experience 3-5 years minimum in software development with production AI/ML projectsPython expert with complex production projectsLangChain/LangGraph: Confirmed production experience (required)n8n: Production workflow experience with complex pipelines (required)RAG/LLM portfolio: Deployed systems, GitHub, technical articlesBonus: TypeScript, Redis, advanced n8n scaling (workers, queues)We offerCompetitive salaryCareer opportunitiesSupportive and caring LeadershipA modern office in the center of ValbonneA chance to work as part of a highly motivated and talented teamReferral programTeam building and Company EventsFree parking