Principal Software Architect, Buliding Ontology

Atlanta, GA - USA

Monthly Salary: Not Disclosed

Posted on: Yesterday

Vacancies: 1 Vacancy

Job Summary

Description

We are looking for a Senior Ontologist to lead the design development and operationalization of buildings ontologies and taxonomies that power data interoperability analytics and intelligent systems across connected buildings products.

This role is hands-on and strategic. You will work at the intersection of domain modeling semantic technologies and standards shaping how complex data is represented connected and consumed at scale.

You will collaborate closely with domain experts data engineers platform architects and product teams to ensure that semantic models are accurate extensible and aligned with industry standards and real-world operational needs.

Responsibilities

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)
- 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.

Standards & Interoperability

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

Applied Semantics & Engineering Collaboration

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.

Architecture Leadership & Strategy

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.

Qualifications

Required Qualifications

Core Expertise

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 model along with structured knowledge of graphs for semantic backbone creation

Technical Skills

Expert-level proficiency in OWL 2 RDF RDFS SPARQL SHACL SKOS JSON-LD and Turtle.Semantic Web Stack:
Deep expertise in at least two of: Neo4j Amazon Neptune Stardog GraphDB Virtuoso Ontotext TigerGraph.Graph Databases:
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.Data Platforms:
Experience with OWL reasoners (Pellet HermiT FaCT) and rule-based systems (SWRL RIF).Reasoning Engines:
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

Required Experience:

Staff IC

DescriptionWe are looking for a Senior Ontologist to lead the design development and operationalization of buildings ontologies and taxonomies that power data interoperability analytics and intelligent systems across connected buildings products.This role is hands-on and strategic. You will work at ...

Description

This role is hands-on and strategic. You will work at the intersection of domain modeling semantic technologies and standards shaping how complex data is represented connected and consumed at scale.

Responsibilities

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)
- 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.

Standards & Interoperability

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

Applied Semantics & Engineering Collaboration

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.

Architecture Leadership & Strategy

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.

Qualifications

Required Qualifications

Core Expertise

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 model along with structured knowledge of graphs for semantic backbone creation

Technical Skills

Expert-level proficiency in OWL 2 RDF RDFS SPARQL SHACL SKOS JSON-LD and Turtle.Semantic Web Stack:
Deep expertise in at least two of: Neo4j Amazon Neptune Stardog GraphDB Virtuoso Ontotext TigerGraph.Graph Databases:
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.Data Platforms:
Experience with OWL reasoners (Pellet HermiT FaCT) and rule-based systems (SWRL RIF).Reasoning Engines:
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

Required Experience:

Staff IC

Key Skills

Kubernetes
S3
Google Cloud Platform
Cassandra
System Architecture
Redshift
AWS
Cloud Architecture
NoSQL
UML
Kafka
Distributed Systems

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About Company

Honeywell

Honeywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability ... View more

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