Lead Knowledge Architect: Graphs, Semantics & AI in Finance

Highbrow LLC

New York (NY)

Hybrid

USD 120,000 - 180,000

Full time

5 days ago
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Job summary

Highbrow LLC is seeking a Lead Knowledge Architect specializing in Knowledge Graphs and AI Semantics for an investment and financial services client. The role focuses on unifying multiple vocabularies used across front office, risk, finance, operations, and compliance to produce consistent and trustworthy AI outputs.

You will design enterprise ontologies, lead cross-department vocabulary reconciliation, and architect scalable graph databases and semantic layers.

Qualifications

  • Must have deep graph and semantic-platform experience.
  • Experience reconciling vocabularies across front office, risk, and finance domains.
  • Proven ability to design enterprise ontologies and knowledge graphs for financial data.

Responsibilities

  • Design and own the enterprise ontology and knowledge graph for instruments, issuers, counterparties, portfolios, positions, transactions, and reference data.
  • Lead cross-departmental vocabulary reconciliation with a governed glossary and semantic layer.
  • Architect and benchmark graph databases and query layers (Neo4j, Neptune, TigerGraph, RDF stores) at financial-data scale.
  • Optimize AI outputs through Graph RAG and hybrid retrieval, entity resolution, grounding and citation strategies.
  • Build knowledge-extraction pipelines from structured and unstructured sources with lineage and quality controls.
  • Act as the client’s semantic authority: facilitate SME workshops and mentor engineers and analysts.

Skills

Knowledge graphs
AI semantics
Investment domain knowledge
Financial services domain

Tools

Neo4j
Amazon Neptune
TigerGraph
RDF/OWL
SHACL
SPARQL
Cypher
Gremlin
Collibra
Alation
Atlan
Python
SQL
Spark
Databricks
Snowflake

Job description

Highbrow LLC is seeking a Lead Knowledge Architect specializing in Knowledge Graphs and AI Semantics for an investment and financial services client. The role focuses on unifying multiple vocabularies used across front office, risk, finance, operations, and compliance to produce consistent and trustworthy AI outputs.

You will design enterprise ontologies, lead cross-department vocabulary reconciliation, and architect scalable graph databases and semantic layers.

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