[Hiring] Lead Specialist, AI Scientist @Pearson

Role Description

We are seeking a Lead Specialist, AI Data & Knowledge Architect to design and build the knowledge foundation of Pearson’s next generation of intelligent K–12 assessment and learning systems. This role sits within the Measurement & Learning team and operates at the intersection of:

• Content Development
• Learning Science
• Technology
• AI Science
• Psychometrics

Responsibilities include translating deep assessment and measurement expertise into extensible computational representations. This work will build a deep, layered knowledge architecture of interconnected graphs beneath our assessment authoring system, grounding the system's AI agents and intelligent workflows, and supporting both formative and summative assessment.

• Standards, competencies, claims, evidence, task designs, scoring, and content will be represented as connected, machine-readable knowledge.
• This is a founding, hands-on role for someone eager to innovate at the edge of current practice.
• The architecture will support predictive, statistical, graph-based, deterministic, and generative AI methods alike.

Qualifications

• Advanced degree in Computer Science, Artificial Intelligence, Information Science, Knowledge Engineering, or a related field, or equivalent experience.
• Demonstrated experience designing and building knowledge graphs in production or substantial applied settings.
• Hands-on experience with knowledge modeling and semantic schema design.
• Strong command of graph and semantic technologies (e.g., RDF, OWL, SHACL, SPARQL, property graphs).
• Strong data architecture skills, including data modeling, integration pipelines, identity, versioning, provenance, and lineage.
• Strong programming ability in Python or comparable languages.
• Deep understanding of predictive and generative AI.
• Track record of building novel systems where no established solution existed.
• Ability to translate expertise from other disciplines into computational representations.

Requirements

• Design and build the knowledge graph and underlying knowledge model for our assessment and learning domains.
• Represent standards, competencies, skills, claims, evidence, task characteristics, misconceptions, content, and their relationships as computationally usable structures.
• Establish approaches for stable identity, versioning, provenance, lineage, and lifecycle status of knowledge objects.
• Evaluate and select graph and semantic technologies based on extensibility, interoperability, reasoning needs, maintainability, and downstream AI use.
• Build the pipelines, mappings, and synchronization processes that connect item banks, standards, metadata, psychometric data, and other sources into a coherent knowledge layer.
• Design retrieval and context architectures that let AI and machine-learning systems use structured knowledge effectively.
• Maintain traceability between AI outputs and the knowledge used to produce them.
• Exercise a high degree of autonomy in shaping architecture where no established blueprint exists.
• Design knowledge systems that make AI reasoning transparent, auditable, and traceable to its sources.
• Partner with Technology teams and software engineers responsible for the assessment authoring system.

Benefits

• Full-time salary range for this role is $140,000 – $160,000.
• This position is eligible to participate in an annual incentive program.

Company Description

This role lays the foundation for an industry-defining assessment system. By making expert knowledge explicit, extensible, and computationally usable, and by inventing new approaches where none exist, this architect will enable more accurate, transparent, and trustworthy generation, alignment, verification, analysis, and guidance across formative and summative assessment.