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.
La descripción completa del puesto cubre todas las habilidades asociadas, la experiencia previa y cualquier cualificación que se espera que tengan los solicitantes.
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).
Responsibilities Build 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.
Requirements Python 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 discussions Have a consultancy mindset → always try to find a solution for the client Work Conditions Type: Full-time & Long-term contract work Start Date: ASAP Location: Remote (99%) in Europe; must be able to travel freely within Europe for workshops. xpzdshu
US Time Zone Overlap: Required (2 PM
- 6 PM CET) Rate: 300-330 EUR/MD If 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!