Our client, a Fortune 50 leader 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 Graph Neural Networks (GNNs) and Generative AI to redefine workflows, semantic search, and intelligence for enterprise solutions in Finance, Operations, Supply Chain, Engineering, or Investments.This is a remote-first position with candidates located in Europe, requiring overlap with US working hours (2-6 PM CET).ResponsibilitiesBuild Agentic Workflows: Implement orchestration, retrieval pipelines, and validator agents using graph-aware tools.Optimize Retrieval: Build hybrid search pipelines (lexical + vector) and integrate vector databases like FAISS, Milvus, or Pinecone.Model Integration: Integrate LLMs (Azure OpenAI, Anthropic) and support domain-specific fine-tuning or adapter models.Scalable Engineering: Develop robust API endpoints and ETL pipelines to support model and agent runtimes.Experiment & Evaluate: Create evaluation suites for reliability, drift detection, and performance optimization.RequirementsPython Expertise: 3+ years of strong Python engineering experience. Graph Intelligence and Databases: 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.Evaluation & Experimentation: Comfortable designing experiments, building eval harnesses, and reasoning about model quality, robustness, and bias in production AI systems.Modern AI Patterns: 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.LLM Observability: Familiarity with LLM evaluation frameworks (e.g., Ragas, DeepEval, Langfuse) and production monitoring of AI systems.Retrieval & Search: Lexical + vector + hybrid retrieval, embeddings, and reranking. Experience incorporating user and context signals for personalization.Fine-tuning & Adaptation: Experience with fine-tuning and adaptation patterns (e.g., LoRA/QLoRA, instruction tuning, embedding model fine-tuning).APIs & Integrations: Solid knowledge of APIs, microservices, and data-centric integrations.Engineering Discipline: Solid software engineering fundamentals - clean code, testing, debugging, code reviews, and comfort working in agile pods.Cloud & Deployment: Experience with AWS/Azure/GCP and CI/CD workflows.Excellent problem-solving skills and keen attention to detail.Ability to participate in the discussions and lead the technical discussionsHave a consultancy mindset → always try to find a solution for the clientWork ConditionsType: Full-time & Long-term contract workStart Date: ASAPLocation: Remote (99%) in Europe; must be able to travel freely within Europe for workshops.US Time Zone Overlap: Required (2 PM - 6 PM CET)Rate: 300-330 EUR/MDIf you are passionate about AI, Graph-centric AI, Python, and building next-generation agentic workflows, this role with our client offers an exciting opportunity to work on cutting-edge R&D projects!

Sourced from LinkedIn. Relocantly aggregates public job postings; apply on the original site.

Senior AI Engineer (Knowledge Graphs & LLMs)