We are seeking a Senior AI Ontology Engineer to support mission-critical programs. This role involves designing, building, and maintaining semantic knowledge frameworks that enable advanced AI/ML reasoning capabilities in highly controlled environments. The ideal candidate has deep expertise in ontology engineering, knowledge graphs, semantic web technologies, and understands the unique constraints of secure data engineering, including semantic data modeling.
### Key Responsibilities
- Design and develop formal ontologies (OWL, RDF/RDFS) to represent complex domain knowledge for defense and intelligence applications
- Build and maintain knowledge graphs that integrate heterogeneous data sources across secure, air-gapped environments
- Implement semantic reasoning engines and inference rules to support AI/ML decision-making and mission planning
- Develop and maintain ontology governance frameworks, including versioning, validation, and quality assurance processes
- Collaborate with data scientists, AI/ML engineers, and mission stakeholders to translate domain requirements into formal semantic models
- Design semantic data integration pipelines that ensure consistency, traceability, and compliance with security standards
- Develop SPARQL queries and semantic APIs to enable knowledge discovery and retrieval across graph databases
- Implement ontology alignment and mapping strategies to ensure interoperability across multiple knowledge systems
- Support the deployment and monitoring of semantic technologies in secure production environments
- Establish and enforce ontology design patterns and best practices in compliance with security requirements
- Mentor junior engineers and promote semantic technology adoption across the organization
- Document ontology architectures, design decisions, and semantic data flows for technical and non-technical stakeholders
- Analyze source data, identify common entities and relationships, and map data across disparate systems
- Bachelor's degree in Computer Science, Information Science, Knowledge Engineering, or a related field
- 5+ years of experience in ontology engineering, knowledge graphs, or semantic data modeling, data engineering, data analysis, or related disciplines
- Hands-on experience with semantic technologies including OWL, RDF, RDFS, SPARQL, and ontology development tools (e.g., Protégé)
- Experience designing and building knowledge graphs, taxonomies, or ontology-driven systems
- Strong understanding of graph databases (e.g., Neo4j, Neptune, Stardog, Blazegraph, GraphDB)
- Proficiency in Python or another programming language used for data processing and integration.
- Knowledge of data security principles, including access control, encryption, and auditing
- Strong analytical and problem-solving skills with attention to semantic precision and logical consistency
- Experience with data modeling, ETL, data integration, or mapping data across multiple source systems.
- Master's degree or PhD in Knowledge Engineering, Semantic Web, Computer Science, or related technical field
- Experience with upper ontologies and domain-specific ontology frameworks (e.g., BFO, DOLCE, CCO)
- Experience with ontology alignment, matching, integration, modularization, or reuse strategies
- Familiarity with semantic data validation frameworks (e.g., SHACL, ShEx)
- Familiarity with ontology governance, versioning, and lifecycle management.
- Knowledge of DoD/IC data standards and compliance frameworks (e.g., RMF, NIST 800-53)
- Experience integrating semantic layers with AI/LLM pipelines for enhanced reasoning
- Experience with semantic web libraries such as RDFLib, OWL API, or Apache Jena.
- Experience with semantic reasoning engines or inference technologies
- Familiarity with Docker, containerization, or deployment in restricted environments.
Pay Information
Full-Time Salary Range: $104900.00 - $194700.00
At Lockheed Martin, we know mission success starts with taking care of our people. Our Total Rewards program is designed to attract top talent, support your well-being, and help you grow—both professionally and personally.
The salary range for this position is as listed on the requisition. Please note that the salary information listed is a general guideline only. Lockheed Martin considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/ training, key skills as well as market(work location) and business considerations when extending an offer.
Benefits offered: Medical, Dental, Vision, Flexible work arrangements and schedules (e.g., 4x10), 401(k) match, Paid time off, Holidays, Parental Leave, EAP, Flexible Spending Accounts, Education Assistance, Life Insurance, Short-Term Disability, and Long-Term Disability.
- Annual short-term and/or long-term incentive compensation programs may be offered depending on the position. Payments under these annual programs are not guaranteed and can vary from year to year and are tied to a range of performance metrics.
- For (Washington state applicants only) Non-represented full-time employees: accrue at least 10 hours per month of Paid Time Off (PTO) to be used for incidental absences and other reasons; receive at least 90 hours for holidays. Represented full time employees accrue 6.67 hours of Vacation per month; accrue up to 52 hours of sick leave annually; receive at least 96 hours for holidays. PTO, Vacation, sick leave, and holiday hours are prorated based on start date during the calendar year.
Skills Required
- Bachelor's degree in Computer Science, Information Science, Knowledge Engineering, or a related field
- 5+ years of experience in ontology engineering, knowledge graphs, semantic data modeling, data engineering, data analysis, or related disciplines
- Hands-on experience with OWL, RDF, RDFS, SPARQL, and ontology development tools such as Protege
- Experience designing and building knowledge graphs, taxonomies, or ontology-driven systems
- Strong understanding of graph databases such as Neo4j, Neptune, Stardog, Blazegraph, or GraphDB
- Proficiency in Python or another programming language used for data processing and integration
- Knowledge of data security principles, including access control, encryption, and auditing
- Strong analytical and problem-solving skills with attention to semantic precision and logical consistency
- Experience with data modeling, ETL, data integration, or mapping data across multiple source systems
- Master's degree or PhD in Knowledge Engineering, Semantic Web, Computer Science, or a related technical field
- Experience with upper ontologies and domain-specific ontology frameworks such as BFO, DOLCE, or CCO
- Experience with ontology alignment, matching, integration, modularization, or reuse strategies
- Familiarity with semantic data validation frameworks such as SHACL or ShEx
- Familiarity with ontology governance, versioning, and lifecycle management
- Knowledge of DoD/IC data standards and compliance frameworks such as RMF or NIST 800-53
- Experience integrating semantic layers with AI/LLM pipelines
- Experience with RDFLib, OWL API, or Apache Jena
- Experience with semantic reasoning engines or inference technologies
- Familiarity with Docker, containerization, or deployment in restricted environments
Lockheed Martin Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Lockheed Martin and has not been reviewed or approved by Lockheed Martin.
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Retirement Support — Retirement benefits are described as a standout element, with a strong 401(k) program and options like an employee stock purchase plan. Feedback suggests these features meaningfully enhance total compensation and long‑term financial security.
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Healthcare Strength — Healthcare coverage is portrayed as comprehensive from day one, with multiple plan options, mental health resources, and virtual care. Wellness supports such as on‑site services and preventive programs are also highlighted.
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Flexible Benefits — Work arrangements often include compressed schedules and telework, contributing to a favorable work‑life balance. Feedback suggests this flexibility is a key reason many view the overall package positively.
Lockheed Martin Insights
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