Principal Software Architect, Building Ontology

Key Responsibilities Ontology & Semantic Model Development

• Design, build, and maintain industrial ontologies, taxonomies, and knowledge models covering assets, spaces, processes, and operational data.
• Develop and extend models aligned with industry standards such as Brick Schema, Project Haystack, ASHRAE 233P, IFC (Industry Foundation Classes), and related building, utilities, energy, or asset-management ontologies.
• Define clear concept hierarchies, relationships, constraints, and naming conventions.
• Conduct ontology alignment and integration with external knowledge bases and domain-specific ontologies.

• Map, align, and reconcile concepts across multiple industry schemas and customer-specific models.
• Design semantic alignment strategies between heterogeneous data sources (BMS, IoT, SCADA, CMMS, ERP, digital twins).
• Ensure models support interoperability, extensibility, and backward compatibility.
• Leverage large language models (e.g., GPT-4, Claude, LLaMA, Mistral) and NLP pipelines to automate ontology population, entity extraction, and relation classification.

• Work closely with data engineering and platform teams to operationalize ontologies in production systems, support semantic querying, reasoning, and metadata-driven pipelines.
• Define best practices for ontology versioning, governance, and lifecycle management.
• Translate abstract semantic models into practical, implementable artifacts.

• Define the long-term technical vision and roadmap for the enterprise semantic and knowledge graph platform.
• Establish architectural standards, design patterns, and reference architectures for semantic data integration across business units.
• Partner with data engineering, ML, product, and business teams to translate domain requirements into graph and semantic models.
• Evaluate and recommend emerging technologies, tools, and open standards in the knowledge graph and AI/LLM landscape.
• Represent the organization in external technical communities, standards bodies, and industry working groups.

• Deep, hands-on experience in ontology engineering and taxonomy design for industrial or building domains.
• Strong working knowledge of Brick Schema, Project Haystack, and IFC (not just theoretical familiarity).
• Proven experience building real-world, production-grade semantic models.
• Understanding of Large Language models along with structured knowledge of graphs for semantic backbone creation.

• Expert-level proficiency in OWL 2, RDF, RDFS, SPARQL, SHACL, SKOS, JSON-LD, and Turtle.
• Deep expertise in at least two of:
  Neo4j, Amazon Neptune, Stardog, GraphDB, Virtuoso, Ontotext, Tiger Graph.
• Familiarity with semantic querying (e.g., SPARQL, CIPHER) and metadata-driven architectures.
• Familiarity with cloud data stacks (AWS, GCP, Azure), Apache Kafka, dbt, Databricks, or Snowflake.
• Experience with OWL reasoners (Pellet, HermiT, FaCT++) and rule-based systems (SWRL, RIF).
• Familiarity with knowledge graph platforms like Palantir Foundry, Microsoft Fabric, or Google Enterprise Knowledge Graph.
• Ability to collaborate effectively with software and data engineers.
• Understanding of how industrial systems generate, structure, and consume data.
• Experience with digital twins, asset modeling and systems engineering.
• Experience designing ontology governance frameworks on a scale.
• Ability to evaluate and integrate open vs proprietary semantic models.
• Prior experience in a platform, product, or enterprise-scale environment.
• Experience working in a fast-paced technology environment focused on delivering a world class product within an agile methodology utilizing latest technology frameworks.

Honeywell is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, religion, or veteran status.