Knowledge Engineer

Company : Govini

Job Type : Full Time

Pittsburgh, Pennsylvania

Number of Applicants

000+

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Job Description - Knowledge Engineer

Company Description

Govini transforms Defense Acquisition from an outdated manual process to a software-driven strategic advantage for the United States. Our flagship product, Ark, supports Supply Chain, Science and Technology, Production, Sustainment, Logistics, and Modernization teams with AI-enabled Applications and best-in-class data to more rapidly imagine, develop, and field the capabilities we need. Today, the national security community and every branch of the military rely on Govini to enable faster and more informed Acquisition decisions.

Job Description

We are seeking a Knowledge Engineer to join our Data Product & Operations team. In this role, you will build and maintain taxonomies, controlled vocabularies, and domain ontologies that bring structure to complex defense acquisition data. Working alongside data engineers and data scientists, domain experts, and product teams, you'll create semantic models that provide structured knowledge to AI systems and enable effective search, classification, and analysis across Govini's Ark platform.

This role requires systematic analytical thinking, strong communication skills, and a passion for combining theoretical rigor with practical implementation. The ideal candidate brings hands-on experience in taxonomy and ontology development, along with the ability to guide teams in adopting semantic technologies.

This role is a full-time position located out of our office in Pittsburgh, PA.

This role may require up to 10% travel

Scope of Responsibilities

Build and maintain ontologies, taxonomies, and controlled vocabularies for defense acquisition domains

Map unstructured data to structured semantic models that integrate with Ark's data infrastructure

Establish metadata standards and modeling guidelines in collaboration with data engineering and data science teams

Partner with product and domain experts to translate business requirements into semantic solutions

Document semantic models and provide guidance to support team adoption and effective use

Help drive organization-wide understanding and adoption of semantic technologies and best practices.

Track adoption and measure impact, continuously refining models, tools, and practices

Qualifications

U.S. Citizenship is required

Required Skills:

Bachelor’s degree in Data Science, Computer Science, Information Systems, or a related field

3+ years of experience developing ontologies, taxonomies, or knowledge graphs

Hands-on experience with ontology editors (e.g., Protégé, TopBraid) and graph databases (e.g., Neo4j, RDF stores)

Working knowledge of semantic web standards (OWL, RDF, SKOS, SPARQL)

Proven ability to collaborate with technical and non-technical stakeholders to translate requirements into semantic models

Desired Skills:

Understanding of how AI/ML and generative AI systems leverage structured knowledge and ontologies

Active U.S. security clearance or ability to obtain one

Experience in or exposure to the nuances of a startup or other entrepreneurial environment

Master’s degree in Data Science, Computer Science, Information Systems, or a related field

Familiarity with defense acquisition data and processes

Experience with data modeling, schema design, or metadata management

We firmly believe that past performance is the best indicator of future performance. If you thrive while building solutions to complex problems, are a self-starter, and are passionate about making an impact in global security, we’re eager to hear from you.

Govini is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans status or any other characteristic protected by law.

Original job Knowledge Engineer posted on GrabJobs ©. To flag any issues with this job please use the Report Job button on GrabJobs.

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