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Knowledge Engineering Jobs in Virginia (NOW HIRING)

Senior AI Engineer

Dahlgren, VA · On-site

$106K - $146K/yr

... knowledge graph solutions in support of defense mission engineering programs. The ideal candidate will translate complex, multi-domain mission requirements into scalable knowledge representations and ...

... knowledge engineering, industry expertise, or legacy evolution. -Interacts with the customer to gain an understanding of the business environment and technical context. -Validates scope, plans, and ...

Knowledge Manager

Reston, VA · On-site

$55K - $126K/yr

Knowledge Manager The Opportunity: The right interface can make a site easy to use, encourage early ... We're looking for you, a web developer who will use equal parts skill and vision to create an ...

Knowledge Manager

Lorton, VA · On-site

$55K - $126K/yr

Knowledge Manager The Opportunity: The right interface can make a site easy to use, encourage early ... We're looking for you, a web developer who will use equal parts skill and vision to create an ...

Knowledge Manager

Mclean, VA · On-site

$55K - $126K/yr

Knowledge Manager The Opportunity: The right interface can make a site easy to use, encourage early ... We're looking for you, a web developer who will use equal parts skill and vision to create an ...

Knowledge Manager

Fairfax, VA · On-site

$55K - $126K/yr

Knowledge Manager The Opportunity: The right interface can make a site easy to use, encourage early ... We're looking for you, a web developer who will use equal parts skill and vision to create an ...

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Knowledge Engineering information

What does a knowledge engineer do?

A knowledge engineer designs, develops, and maintains systems that capture and organize knowledge for artificial intelligence and expert systems. They analyze domain data, create ontologies, and implement knowledge bases using tools like logic programming and semantic technologies. Strong analytical skills and understanding of data modeling are essential for this role.

What is knowledge engineering?

Knowledge engineering is a field within artificial intelligence that focuses on creating systems capable of simulating human decision-making and reasoning. It involves gathering, organizing, and structuring information so that computers can use it to solve complex problems. Knowledge engineers work to build knowledge bases and rule-based systems, often collaborating with domain experts to codify expertise into a form that machines can process. This discipline is fundamental in the development of expert systems, intelligent agents, and modern AI applications.

What is the difference between Knowledge Engineering vs Data Scientist?

AspectKnowledge EngineeringData Scientist
Required CredentialsTypically degrees in computer science, AI, or related fields; certifications in knowledge systemsDegrees in statistics, computer science, or mathematics; certifications in data analysis or machine learning
Work EnvironmentDeveloping knowledge bases, expert systems, and AI applications in tech or research settingsAnalyzing data, building predictive models, and deriving insights in various industries
Employer & Industry UsageUsed in AI development, research institutions, and tech companiesUsed across finance, healthcare, marketing, and tech sectors

While both roles involve working with data and AI, Knowledge Engineers focus on creating structured knowledge bases and expert systems, whereas Data Scientists analyze data to extract insights and build predictive models. Understanding these differences helps in choosing the right career path or job focus.

How does a knowledge engineer typically collaborate with subject matter experts during a project?

Knowledge Engineers frequently work closely with subject matter experts (SMEs) to extract, structure, and formalize domain knowledge into usable formats for AI systems or knowledge bases. This collaboration often involves conducting interviews, facilitating workshops, and reviewing documentation to ensure complex concepts are accurately captured. Effective communication and iterative feedback are key, as Knowledge Engineers must bridge the gap between technical requirements and expert insights. This teamwork helps ensure that the resulting system is both technically sound and aligned with real-world practices.

How much does a knowledge engineer make?

A knowledge engineer's salary typically ranges from $70,000 to $130,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in AI, machine learning, or data management can earn higher salaries. Many positions also require proficiency with tools like ontologies, semantic web technologies, and knowledge representation languages.

What are the key skills and qualifications needed to thrive as a knowledge engineer?

To thrive as a Knowledge Engineer, you need a strong background in computer science, logic, and data modeling, often supported by a relevant degree. Familiarity with knowledge representation systems, ontologies, semantic web technologies, and tools like Protégé is typically required, along with experience in programming languages such as Python or Java. Strong analytical thinking, problem-solving abilities, and clear communication skills help you collaborate with subject matter experts and translate complex information into structured formats. These skills are critical for building effective knowledge-based systems that drive intelligent decision-making and organizational efficiency.
What job categories do people searching Knowledge Engineering jobs in Virginia look for? The top searched job categories for Knowledge Engineering jobs in Virginia are:
Infographic showing various Knowledge Engineering job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 18% Part Time, 1% Temporary, and 3% Contract. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution.

$106K - $146K/yr

Full-time

Medical, Retirement, PTO

Re-posted 13 days ago


Job description

TSC is seeking a Senior Ontology Engineer in King George/Dahlgren, Virginia. This position supports the Systems Engineering & Analysis Division (SEA).

*Ability to obtain and maintain a SECRET DoD Clearance.

TSC offers a professional working environment, a competitive salary, and an excellent benefits package. Come and join our team!

We are seeking a Senior Ontology Engineer to design, develop, and maintain ontological frameworks and knowledge graph solutions in support of defense mission engineering programs. The ideal candidate combines deep expertise in formal ontology and semantic web technologies with hands-on experience in data integration, graph database systems, large language models, and knowledge-driven data architecture development. This individual will translate complex, multi-domain mission requirements into scalable knowledge representations and work alongside software engineers, systems engineers, and domain experts to deliver end-to-end solutions. The ideal candidate has experience in technical writing and will work alongside the business development team to propose innovative solutions to address requests for proposals.

Responsibilities:

This position is designed to be flexible, with responsibilities evolving to meet program needs, emerging technology trends, and opportunities for individual professional growth.

This position requires a technically deep and mission-focused individual with expertise in knowledge engineering, ontology development, and artificial intelligence technologies applied to defense and mission engineering domains.

Design, develop, and maintain formal ontologies using OWL, RDF/RDFS, and SPARQL aligned with DoD mission engineering requirements and semantic interoperability standards.
Build and deploy knowledge graph solutions that integrate structured and unstructured data sources across heterogeneous, multi-domain defense systems.
Apply and extend upper-level ontology frameworks, ensuring alignment with DoD and IC data standards.
Design and implement graph-based AI and semantic solutions, including LLM-integrated pipelines, RAG architectures, and agentic workflows that leverage knowledge graph representations.
Collaborate with engineers, systems architects, and mission-domain SMEs to translate operational requirements into actionable ontological models and knowledge architectures.
Support semantic integration and data interoperability efforts across legacy and modern system architectures, including graph database deployments (e.g., Stardog, Neptune, Neo4j).
Lead the development and writing of technical approaches for proposals related to supporting the Navy adopt AI technologies

Required Qualifications:

  • Bachelor's degree or higher in Computer Science, Information Science, Knowledge Engineering, or a related discipline; equivalent experience considered

  • PhD with 2+ years of relevant experience, MA/MS with 5+ years of relevant experience, or BA/BS with 7+ years

    • Hands-on experience with knowledge graph technologies including RDF, SPARQL, SHACL, and OWL for DoD or enterprise use cases

    • Experience with schema design, ontology management, and knowledge graph curation

    • Experience designing and developing end-to-end knowledge graph and AI data pipelines, including integration with LLMs or similar models

    • Familiarity with graph database platforms such as Stardog, Blazegraph, Neo4j, or Amazon Neptune

  • Ability to obtain and maintain a SECRET DoD Clearance

Preferred Qualifications:

  • Experience with U.S. Navy Combat Systems

  • 2+ years of hands-on Python experience, including frameworks such as TensorFlow, PyTorch, rdflib, or owlready2, and ETL pipeline tools (e.g., Apache NiFi, Airflow)

  • Experience with full-stack web development, including REST API design and development (e.g., FastAPI, Flask, or Node.js), front-end frameworks (e.g., React or Angular), and containerization/deployment tooling (e.g., Docker, Kubernetes)

  • Practical experience with NLP, semantic search, prompt engineering, and LLMs for enterprise-scale knowledge graph applications including RAG architectures.

  • Experience with agentic AI systems and multi-modal model integration applied to knowledge engineering problems

  • Demonstrated team leadership experience, with the ability to guide junior engineers and collaborate across engineering, research, and program management teams

  • PhD in Computer Science, Knowledge Engineering, Mathematics, or a related field, or a publication record in semantic web and knowledge representation

U.S. Citizenship Required for this Position: Yes

Job Type:Regular

Security Clearance: Secret (ability to obtain required)

Schedule:Full time (40 hr/week)

Travel:0-10%

TSC Benefits:

TSC offers a stable work environment, a competitive salary, and a comprehensive benefit package; including ESOP participation, 401k Plan, Flexible Work Schedules, Tuition Reimbursement, Co-Sponsored Health Plan, Paid Leave and much more.

Applying to TSC:

Only those candidates invited for an interview will be contacted. Employment at TSC is contingent upon the successful completion of a comprehensive background check, security investigation, and a drug screening.


This contractor and subcontractor shall abide by the requirements of 41 CFR 60-1.4(a), 60-300.5(a) and 60-741.5(a). These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity, national origin, or for inquiring about, discussing, or disclosing information about compensation. Moreover, these regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.