Senior Knowledge Graph & LLM Architect (Hybrid)

Biorce; Austin (TX); Hybrid; USD 150,000 - 190,000; Full time

Benefits offered by this job

Hybrid work model

Private health coverage

Gym membership

MacBook provided

Company events

Snacks

Job summary

Biorce is seeking a Senior Research/AI Engineer to design and evolve knowledge graphs with RDF/OWL, integrating LLMs to power KG-driven AI. You will collaborate with data scientists, ML engineers, and product teams to build scalable, explainable AI solutions.

Ideal candidates have 3+ years building production KG systems, strong ontology expertise, and hands-on experience with graph databases like Neo4j or AWS Neptune. A hybrid work model is offered.

Qualifications

• 3+ years designing and implementing large-scale Knowledge Graphs in production.
• Deep expertise in ontology engineering, semantic modeling (RDF, RDFS, OWL) and SPARQL.
• Proficiency with at least one major graph database (Neo4j, TigerGraph, AWS Neptune).
• Experience integrating LLMs with Knowledge Graphs (RAG, KG-powered AI agents).
• Strong programming skills in Python.
• NLP techniques for text processing and structuring (NER, relation extraction).
• Excellent communication and collaboration in fast-paced Agile environments.

Responsibilities

• Design and evolve ontology and semantic models for our knowledge graph (RDF/OWL).
• Build and optimize knowledge graph architecture with graph databases.
• Write high-performance graph queries (Cypher, SPARQL) and perform analytics.
• Collaborate with Data Scientists, ML Engineers and Product Managers to translate requirements into KG solutions.
• Monitor and tune graph pipelines for scalability and real-time query speed.

Skills

Knowledge Graphs

Ontology Engineering

Graph Databases

Python

NLP techniques

LLMs integration

Communication

Team collaboration

Education

Master's or Ph.D. in Computer Science/AI

Tools

Neo4j

TigerGraph

AWS Neptune

Job description

Biorce is seeking a Senior Research/AI Engineer to design and evolve knowledge graphs with RDF/OWL, integrating LLMs to power KG-driven AI. You will collaborate with data scientists, ML engineers, and product teams to build scalable, explainable AI solutions.

Ideal candidates have 3+ years building production KG systems, strong ontology expertise, and hands-on experience with graph databases like Neo4j or AWS Neptune. A hybrid work model is offered.