Lead Specialist, AI Scientist

• Advanced degree in Computer Science, Artificial Intelligence, Information

• Strong understanding of how educational knowledge is structured, through K–12

standards, competency frameworks, or skills-based architectures such as skills taxonomies and credential frameworks, ideally from modeling them as structured data

• Experience with knowledge graphs that power applications such as content

• Design and build the knowledge graph and underlying knowledge model for our

assessment and learning domains, selecting among ontologies, schemas, vocabularies, and taxonomies as the problem requires

• Represent standards, competencies, skills, claims, evidence, task

characteristics, misconceptions, content, and their relationships as computationally usable structures

• Design for extensibility across content areas, programs, assessment contexts,

and future AI capabilities, starting simple without closing off future growth

• Establish approaches for stable identity, versioning, provenance, lineage,

• Clearly separate authoritative knowledge, expert judgments, derived

information, and machine-generated hypotheses

• Evaluate and select graph and semantic technologies based on extensibility,

• Build the pipelines, mappings, and synchronization processes that connect

item banks, standards, metadata, psychometric data, and other sources into a coherent knowledge layer

• Develop the schemas, APIs, data contracts, and services through which

applications, agents, and analytic workflows access the knowledge architecture

• Partner with software engineers to integrate the knowledge layer into our

assessment authoring system

• Design retrieval and context architectures that let AI and machine-learning

systems use structured knowledge effectively, including graph, semantic, vector, and hybrid retrieval

• Create task-specific knowledge projections so each capability receives what

it needs without complex relationships being flattened into unstructured prompts

• Maintain traceability between AI outputs and the knowledge used to produce

• Work with Applied AI Systems Engineers to ensure generative, predictive,

agentic, and analytic capabilities operate reliably over the shared knowledge layer

• Exercise a high degree of autonomy in shaping architecture where no

• Prototype quickly, test assumptions empirically, and change course when

• Evaluate emerging approaches, including graph-based, knowledge-grounded, and

• Make architectural decisions, assumptions, and tradeoffs explicit and open to

challenge from colleagues

• Design knowledge systems that make AI reasoning transparent, auditable, and

• Support AI that strengthens human expertise rather than replacing it, with

• Partner with AI engineers, psychometricians, and content experts to test

whether knowledge and retrieval designs measurably improve accuracy and reliability

• Establish quality, coverage, and consistency measures for knowledge assets
• Uphold responsible data practices, including privacy, security, access

control, and appropriate use of student and content data

• Partner with Technology teams and software engineers responsible for the

• Co-design architecture with AI Science colleagues and Applied AI Systems

• Partner with psychometricians and learning scientists to represent

• Work with content development teams and subject-matter experts to capture

• Communicate complex architectural concepts clearly to technical and

non-technical audiences

• Demonstrated experience designing and building knowledge graphs in production

• Hands-on experience with knowledge modeling and semantic schema design, using

approaches such as ontologies, property-graph schemas, vocabularies, and taxonomies

• Strong command of graph and semantic technologies (e.g., RDF, OWL, SHACL,

• Strong data architecture skills, including data modeling, integration

• Strong programming ability in Python or comparable languages, with a record

• Deep understanding of predictive and generative AI, including how

• Track record of building novel systems where no established solution existed,

• Ability to translate expertise from other disciplines into computational

representations and to communicate tradeoffs clearly.

• Experience with formal ontology engineering, including OWL-based modeling,

• Experience building hybrid AI systems that combine machine-learned or

generative models with structured knowledge, rules, or constraints, including neuro-symbolic approaches

• Experience with graph machine learning, graph embeddings, link prediction, or

• Experience in domains where outputs must be validated against reliable

evidence or expert judgment, such as scientific, healthcare, financial, or legal AI

• Experience with evaluation datasets, human annotation and adjudication

• Familiarity with educational measurement, psychometrics, principled

• Publications, patents, or open-source contributions in knowledge

representation or graph technologies

• Knowledge as a durable, extensible organizational asset
• Build to learn: prototype, measure, iterate
• Innovation at the edge of current practice, grounded in evidence
• Transparent, auditable, and traceable AI reasoning
• AI that supports rather than supplants human expertise
• The right method for the problem, not the newest one

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.

Compensation at Pearson is influenced by factors including skill set, experience, and location.

The full-time salary range for this role is $140,000 – $160,000. This position is eligible to participate in an annual incentive program. Information on benefits can be found here [https://pearsonbenefitsglobal.com/].

Applications will be accepted through 20th November 2026. This window may be extended depending on business needs.

Apply today and imagine the impact you can make.