AI Knowledge Architect for Assessment & Learning

Pearson; Baton Rouge (LA); On-site; USD 140,000 - 160,000; Full time

Job summary

Pearson is seeking a Lead Specialist, AI Data & Knowledge Architect to build the knowledge foundation for its next generation of K–12 assessment systems. You will shape an extensible, computable knowledge layer that underpins AI agents, retrieval, and analytics across assessment contexts.

The role combines AI, measurement science, data architecture, and software integration, requiring autonomy to prototype, validate, and iterate in a fast-moving, cross-disciplinary environment.

Qualifications

• Advanced degree or equivalent experience in a related field.
• Demonstrated experience designing and building knowledge graphs in production.
• Hands-on knowledge modeling and semantic schema design (ontologies, vocabularies, taxonomies).
• Strong command of graph & semantic technologies (RDF/OWL/SPARQL) and architectural tradeoffs.

Responsibilities

• Design and build the knowledge graph and underlying knowledge model for assessment domains.
• Represent standards, competencies, skills, claims, evidence, and task characteristics as computational structures.
• Design for extensibility across content areas and future AI capabilities.
• Establish provenance, versioning, and lifecycle status of knowledge objects.

Skills

Python programming

Knowledge graphs

Graph technologies

Semantic modeling

Data architecture

Architecture design

Education

Advanced degree in CS / AI / Information Science / Knowledge Engineering

Tools

RDF/OWL/SPARQL

SHACL

Property graphs

Job description

Pearson is seeking a Lead Specialist, AI Data & Knowledge Architect to build the knowledge foundation for its next generation of K–12 assessment systems. You will shape an extensible, computable knowledge layer that underpins AI agents, retrieval, and analytics across assessment contexts.

The role combines AI, measurement science, data architecture, and software integration, requiring autonomy to prototype, validate, and iterate in a fast-moving, cross-disciplinary environment.