ppOur client, a bFortune 50 leader /b in enterprise solutions and innovations, is seeking a Senior AI Engineer with Knowledge Graphs and LLMs skills to join their AI incubator to scout, incubate, and validate internal ideas. This role is part of a high-impact strategy leveraging bGraph Neural Networks (GNNs) and Generative AI /b to redefine workflows, semantic search, and intelligence for enterprise solutions in Finance, Operations, Supply Chain, Engineering, or Investments. /ppThis is a bremote-first position with candidates located in Europe, /b requiring overlap with bUS working hours (2-6 PM CET). /b /ph3Responsibilities /h3ullibBuild Agentic Workflows: /b Implement orchestration, retrieval pipelines, and validator agents using graph-aware tools. /lilibOptimize Retrieval: /b Build hybrid search pipelines (lexical + vector) and integrate vector databases like FAISS, Milvus, or Pinecone. /lilibModel Integration: /b Integrate LLMs (Azure OpenAI, Anthropic) and support domain-specific fine-tuning or adapter models. /lilibScalable Engineering: /b Develop robust API endpoints and ETL pipelines to support model and agent runtimes. /lilibExperiment Evaluate: /b Create evaluation suites for reliability, drift detection, and performance optimization. /li /ulh3Requirements /h3ullibPython Expertise: /b 3+ years of strong Python engineering experience. /lilibGraph Intelligence and Databases: /b Working knowledge of knowledge graph modeling (schemas, ontologies, entity resolution) and graph databases. Hands-on experience with Neo4j, Memgraph, AWS Neptune, ArangoDB, or similar. Familiarity with graph embeddings and GNNs (GCN/GAT) is a plus. /lilibEvaluation Experimentation: /b Comfortable designing experiments, building eval harnesses, and reasoning about model quality, robustness,



and bias in production AI systems. /lilibModern AI Patterns: /b Hands-on experience building RAG pipelines and agentic workflows. Comfort with prompt engineering and tool/function calling. Experience building text-to-SQL or semantic parsing capabilities over structured data sources. /lilibLLM Observability: /b Familiarity with LLM evaluation frameworks (e.g., Ragas, DeepEval, Langfuse) and production monitoring of AI systems. /lilibRetrieval Search: /b Lexical + vector + hybrid retrieval, embeddings, and reranking. Experience incorporating user and context signals for personalization. /lilibFine-tuning Adaptation: /b Experience with fine-tuning and adaptation patterns (e.g., LoRA/QLoRA, instruction tuning, embedding model fine-tuning). /lilibAPIs Integrations: /b Solid knowledge of APIs, microservices, and data-centric integrations. /lilibEngineering Discipline: /b Solid software engineering fundamentals - clean code, testing, debugging, code reviews, and comfort working in agile pods. /lilibCloud Deployment: /b Experience with AWS/Azure/GCP and CI/CD workflows. /lilibExcellent problem-solving skills /b and keen attention to detail. /liliAbility to bparticipate in the discussions /b and lead the technical discussions /lilibHave a consultancy mindset /b always try to find a solution for the client /li /ulh3Work Conditions /h3ullibType: /bFull-time Long-term contract work /lilibStart Date /b: ASAP /lilibLocation /b: Remote (99%) in Europe; must be able to travel freely within bEurope /b for workshops. /lilibUS Time Zone Overlap /b: Required (b2 PM - 6 PM CET /b) /li /ulpIf you are passionate about bAI, Graph-centric AI /b, bPython /b, and building next-generation bagentic workflows /b, this role with our client offers an exciting opportunity to work on cutting-edge RD projects! /p /p #J-18808-Ljbffr

📌 Senior AI Engineer (Knowledge Graphs & LLMs) (Italia)
🏢 Jimmy Technologies
📍 Italia