Lead Ontology & Knowledge Engineer

Overview

Pratt & Whitney is at the forefront of transforming the future of flight, and we're looking for a highly skilled Lead Ontology & Knowledge Engineer to drive this innovation. This remote role involves architecting the logic that powers our digital workforce and enabling advanced AI capabilities within our organization.

The Mission

Our goal is to build the central nervous system for AI at Pratt & Whitney, deploying autonomous AI agents capable of complex reasoning, decision support, and automation. As the Lead Ontology & Knowledge Engineer, you will be crucial in constructing the semantic layer – the Knowledge Graph – providing agents with the context needed to understand relationships between critical aerospace elements like engine parts, maintenance schedules, and supply chain constraints.

What You Will Do

You will bridge the gap between structured and unstructured enterprise data and our LLM-powered agents. Your work will involve designing, implementing, and maintaining the ontologies that serve as the "ground truth" for Pratt & Whitney, moving beyond simple RAG (Retrieval-Augmented Generation) towards GraphRAG, enabling multi-hop reasoning and causal analysis.

Key Responsibilities

• Ontology & Schema Design: Develop and maintain enterprise-grade ontologies (OWL/RDF) modeling complex domains like aerospace engineering, manufacturing, and supply chain. Define semantic schemas for AI Agents, ensuring consistent vocabulary across business units.
• Knowledge Graph Implementation: Lead the architecture and deployment of the Enterprise Knowledge Graph. Build Python data pipelines to ingest data from legacy ERP, PLM software, and unstructured documents. Implement Entity Resolution and linking strategies.
• Context Engineering for AI Agents: Collaborate with AI Engineers to design "Context Windows" for LLMs, determining optimal graph data injection for agent accuracy. Work on Causal Inference models to help agents distinguish correlation from causation.
• Governance & Standards: Establish semantic standards and data governance policies for the AI ecosystem. Evangelize Knowledge Graphs within Pratt & Whitney and train other developers on graph-based thinking.

Qualifications You Must Have

• Bachelor’s degree in Computer Science, Information Science, Mathematics, or a related field with 10+ years of relevant experience; OR a Master's degree with 8+ years of relevant experience; OR a PhD with 5+ years of relevant experience.
• 5+ years of experience in Ontology Engineering, Knowledge Representation, or Data Modeling.
• Proficiency in Graph Query Languages (SPARQL, Cypher, Gremlin).
• Strong coding skills in Python.
• Experience with semantic web standards (RDF, OWL, SKOS, SHACL).
• Experience working with LLMs, Vector Databases, and RAG architectures.
• U.S. citizenship is required.

Desired Qualifications

• Experience in manufacturing, aerospace, or complex supply chain environments is a strong plus.

Work Arrangement

This is a Remote role, with employees primarily working offsite (from home). Candidates may be asked to attend select steps of the interview process in-person at one of our office locations.

Key Skills/Competency

• Ontology Engineering
• Knowledge Graph
• Semantic Web Standards (RDF, OWL)
• Graph Query Languages (SPARQL, Cypher)
• Python Programming
• AI Agents
• LLM Integration
• Data Modeling
• Causal Inference
• Enterprise Data Architecture