Knowledge Graph & Semantic AI Engineer

About the Role

We are looking for an engineer with production experience in knowledge graphs, entity resolution, graph data platforms or related systems to build ExperGo's entity, relationship and semantic intelligence layer.

What You Will Do

• Build production knowledge graphs representing financial entities and relationships
• Develop entity-resolution and record-linkage systems
• Design graph schemas and domain ontologies
• Build graph ingestion, traversal, and query capabilities
• Develop network analytics and graph algorithms
• Identify connected entities, clusters, and unusual network structures
• Model temporal relationships and events
• Maintain evidence, provenance, and confidence behind relationships
• Build semantic retrieval and Graph RAG capabilities
• Expose graph intelligence to ExperGo applications and AI agents through APIs/services

Production Experience Required

You should have experience building or operating graph, entity-resolution, or semantic systems in production, not just academic graph projects.

You should understand:

Graph Data Modelling • High-volume Ingestion • APIs • Query Performance • Indexing • Data Quality • Versioning • Monitoring • Scalability • Security • Deployment • Failure Handling

You should be comfortable designing graph systems that evolve as millions of entities, relationships and events are continuously added or updated.

Skills We Value

Core:

Python • Entity Resolution/Record Linkage • Knowledge Graphs • Graph Modelling • Graph Algorithms • Network Analysis • Production Engineering

Useful:

Neo4j • Cypher • NetworkX • Ontologies • NLP/NER • Graph Embeddings • Temporal Graphs • Graph RAG • Vector Search • RDF/OWL/SPARQL • Docker • Cloud

What We Are Looking For

You should naturally think in terms of:

Entities Relationships Events Evidence Time

Experience with fraud networks, AML/financial crime, Customer 360, identity resolution, master data or financial-services graphs is particularly valuable.