Job Description
Knowledge Engineering & Semantic Modeling: Expertise in formal design of Enterprise Knowledge Bases using OWL/RDF, Ontologies, and Taxonomies.
Information Architecture: Proven ability in content modeling, metadata schemas, and hierarchical categorization rules to transform raw data into structured Knowledge Graphs.
Semantic Search & RAG: Mastery of Retrieval-Augmented Generation, including advanced chunking, hybrid retrieval, and evaluation frameworks for Grounding and Relevance.
Graph & Vector Databases: Hands-on experience with tools like Neo4j, Amazon Neptune, or Stardog, and vector stores like ChromaDB or Pinecone.
Data Integration & APIs: Expert in Python-based ingestion pipelines and normalizing data from enterprise sources like SharePoint, Confluence, and ServiceNow.
Regulated Environments: Experience ensuring scalability, security (IAM), and Responsible AI (Guardrails) within financial sector standards.