This is a full-time position to be worked out of our Tucson, Arizona office.

Job Summary:

In this dynamic role, you will be responsible for constructing symbolic representations of domain-specific knowledge, leveraging domain ontologies to model intricate concepts and relationships. You will be instrumental in driving the progression of advanced knowledge systems technologies, including knowledge representation, ontology design, and graph-based querying. Your role is not only pivotal for our technical advancements but also for ensuring these innovations are seamlessly integrated into our Knowledge System. Acting as a bridge between sophisticated knowledge engineering concepts and our knowledge system, you'll make these technologies accessible and actionable for our users.

Key Responsibilities: 

• Design symbolic representations of domain knowledge, using formalisms such as semantic networks, frames, and rules.
• Craft ontologies to model concepts, relationships, properties, and classes within specific domains.
• Utilize inference engines and reasoning techniques to gain insights, employing deductive, inductive, and abductive reasoning.
• Analyze large datasets for crucial insights and maintain expertise in database management and data modeling.
• Clearly convey tech details to non-experts and collaborate with teams to realize knowledge-based solutions.
• Understand user needs and craft knowledge-based, intuitive solutions using UX principles.
• Tackle challenges using critical thinking and knowledge engineering techniques.
• Aim for excellence and accuracy in all tasks, ensuring knowledge modeling reliability.

Minimum Qualifications:

• Bachelor’s degree in Computer Science, Information Systems, Artificial Intelligence, Semantic Web Technologies, or a related field.
• 3 years of professional experience or 5-7 years of applied research experience in building and maintaining knowledge graphs, ontologies, and semantic infrastructures.
• Solid understanding of knowledge graph technologies, knowledge graph standards, and ontology.
• Proficiency in graph query languages such as SPARQL or Cypher.
• Strong grasp of semantic technologies, RDF, OWL, and related standards.
• Familiarity with ontology development tools such as Protégé.
• Exceptional analytical thinking, problem-solving skills, and attention to detail.
• Ability to collaborate effectively with diverse teams, including data scientists, product managers and software developers.
• Proficiency in programming languages like Python, and technologies used in knowledge systems.