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Knowledge Engineering Jobs in Texas (NOW HIRING)

NextGen Security LLC

Installer

Arlington, TX · On-site

$45K - $51K/yr

... knowledge, engineering design, implementation, management and on-going maintenance services. Our company accomplishes this by hiring only the most experienced and best-qualified talent the security ...

NextGen Security LLC

Project Manager

Arlington, TX · On-site

More About Us NextGen Security is an electronic security systems integrator that offers commercial and industrial companies best in class industry knowledge, engineering design, implementation ...

NextGen Security LLC

Senior Account Manager

Austin, TX · On-site

... knowledge for a broad range of products, working with operations and engineering on a regular basis to develop proposals and management of client security initiatives. Some overnight and out of town ...

NextGen Security LLC

Senior Technician

Houston, TX · On-site

More About Us NextGen Security is an electronic security systems integrator that offers commercial and industrial companies best in class industry knowledge, engineering design, implementation ...

Turner & Townsend

Construction Estimator

Houston, TX · On-site

Aspen Tech knowledge * Engineering/Construction Management Degree * On-site experience * Self-started/ Career Driven/ Well Organized * Must reside in continental United States Additional Information

Turner & Townsend

Construction Estimator

Houston, TX · On-site

Aspen Tech knowledge * Engineering/Construction Management Degree * On-site experience * Self-started/ Career Driven/ Well Organized * Must reside in continental United States Additional Information

Turner & Townsend

Construction Estimator

Houston, TX

Aspen Tech knowledge * Engineering/Construction Management Degree * On-site experience * Self-started/ Career Driven/ Well Organized * Must reside in continental United States Additional Information

New

HBK Engineering, LLC

Engineering Specialist

Spring, TX · On-site

This role involves applying broad knowledge of engineering principles and practices while independently evaluating, selecting, and adapting standard techniques and procedures to address unique and ...

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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 information, create ontologies, and use tools like knowledge bases and reasoning algorithms to enable machines to simulate human decision-making. Strong skills in logic, data modeling, and programming 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 engineers make $500,000 a year?

Highly experienced engineers in specialized fields such as software engineering, data engineering, or systems architecture can earn $500,000 or more annually, especially in senior or executive roles at large technology companies. These positions often require advanced skills, certifications, and extensive industry experience, and may include bonuses and stock options that contribute to total compensation.

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.

What engineers make 200,000 a year?

Senior knowledge engineers, especially those with expertise in artificial intelligence, machine learning, and data science, can earn $200,000 or more annually. High salaries are often associated with extensive experience, advanced certifications, and working in industries like technology, finance, or consulting, typically in roles involving complex problem-solving and specialized tools.

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 require proficiency with knowledge representation, ontologies, and tools like Protégé or OWL.

What are the key skills and qualifications needed to thrive as a Knowledge Engineer, and why are they important?

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 are popular job titles related to Knowledge Engineering jobs in Texas? For Knowledge Engineering jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Knowledge Engineering jobs in Texas look for? The top searched job categories for Knowledge Engineering jobs in Texas are:
What cities in Texas are hiring for Knowledge Engineering jobs? Cities in Texas with the most Knowledge Engineering job openings:
Knowledge Engineering jobs near you
Ontologist / Knowledge Modeler

Ontologist / Knowledge Modeler

Alltech Consulting Services, Inc.

Dallas, TX • On-site

$54.50 - $70.50/hr

Other

This job post has expired today. Applications are no longer accepted.

Job description

POSITION / TITLE: Ontologist / Knowledge Modeler Location:- Dallas TX-Onsite role FTE Role
Who are we looking for?
We are seeking an experienced Ontologist / Knowledge Modelerwith 5+ years of experience to drive the design and implementation of knowledge graphs, ontologies, and data models for our organization. The ideal candidate will possess hands-on experience with graph database technologies and knowledge modeling, leveragingopen-source toolsfor building scalable, interoperable solutions. Expertise in industry standards such asBanking Industry Architecture Network (BIAN)andMortgage Industry Standards Maintenance Organization (MISMO)is highly desirable.
Responsibilities:
Knowledge Modeling & Ontology Design:
  • Develop ontologies and taxonomies using open-source knowledge graph tools likeApache JenaandRDF4J.
  • Build and refine knowledge graphs for structured data representation, aligning with standards such as BIAN and MISMO.
  • Design scalable architectures for linked data and semantic models, integrating data from multiple sources.
Data Interoperability & Standards Alignment:
  • Ensure data interoperability by aligning ontologies with industry standards and regulatory frameworks.
  • Design metadata schemas and common data vocabularies, leveragingRDFandOWLto enhance data accessibility.
oUse tools likeProtgandTopBraid Composerto define and manage ontology structures.
  • Open-Source Tool Integration:
  • Integrate graph database solutions such asNeo4j,ArangoDB, andBlazegraphfor efficient data querying and management.
  • Employ SPARQL endpoints and graph analytics tools to derive insights from knowledge graphs, using solutions likeGraphDBandJanusGraph.
  • Develop data models that support semantic search, data extraction, and AI-driven recommendations.
Advanced Analytics & Knowledge Representation:
  • Collaborate with AI/ML teams to implement natural language processing and contextual data retrieval using knowledge graphs.
  • Enhance data discovery and search capabilities through graph-based search relevancy and knowledge representation.
Required Skills and Qualifications
Experience:
  • Minimum of 3years in ontology development, knowledge modeling, and graph database management.
  • Proven track record with BIAN, MISMO, and other relevant industry standards.
  • Familiarity with open-source graph databases and their applications in real-time analytics and data interoperability.
Technical Skills:
  • Proficiency inRDF/OWL,SPARQL, andknowledge graph platformslike Neo4j, ArangoDB, and Blazegraph.
  • Experience withknowledge graph visualizationtools likeGraphistryandGephi.
  • Strong programming skills inPythonorJavato implement custom graph applications and integrations.
Domain Knowledge:
  • Expertise in financial services, banking, and/or mortgage industry standards and processes.
  • Knowledge of healthcare or regulatory standards is a plus.
  • Ability to incorporate domain knowledge into semantic models for actionable business insights.
Behavioral Skills
Excellent communication skills for conveying complex concepts to technical and non-technical stakeholders.
Ability to work both independently and within a team setting, showing leadership in best practices.
Proactive, innovative, and detail-oriented, with a strong focus on emerging technologies.
Educational Qualifications
Bachelor s or Master s degree inInformation Science, Data Science, Knowledge Management, or a related field.
Certifications inontology managementordata standardsare highly valued.

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