AI Context and Ontology Development Intern at Marketbridge in Remote

Summary: Marketbridge partners with leading B2B brands to create unified Go-to-Market® systems that connect strategy, AI, creativity, activation and measurement. The intern will work directly with the SVP of Global AI Product Management and Practice AI Leads to build out the firm-wide context layer and ontology, contributing to production work from day one. Responsibilities: - Develop and extend the firm-wide ontology, defining entity types, properties, and relationships that represent how Marketbridge delivers value across practice areas, so AI systems can reason over that structure rather than rely on keyword retrieval alone - Author and refine skill definitions for the AI context layer, establishing the schema that anchors each capability to the right practice domain and engagement type, and building the metadata framework that governs how context flows between agents and tools - Work directly with Practice AI Leads to validate that the ontology reflects how work is actually structured and delivered across the firm, identifying gaps between documented methodology and operating reality and closing them through iterative revision - Work with the global AI product lead to define how institutional expertise, client context, and delivery frameworks should interconnect across the firm, contributing to a knowledge architecture that enables intelligence to move across practices and geographies rather than remain siloed within individual teams - Design an iterative ontology management approach structure based on validation findings, refining entity relationships, resolving classification conflicts, and improving retrieval performance across the AI context layer - Work with the engineering team to research architectural decisions, governance model, and ontology maintenance standards to ensure the context layer remains accurate, auditable, and extensible as the platform evolves, and the firm grows Required Qualifications: - Currently pursuing a graduate or advanced undergraduate degree in artificial intelligence, knowledge engineering, computer science, information science, or a related field with a concentration in ontology, semantic technologies, or knowledge representation - Coursework or project experience in at least two of the following: ontology languages and modeling (OWL, RDF, SKOS), knowledge graph construction, semantic search and retrieval, LLM context window management, RAG architecture, or AI agent design and orchestration - Demonstrated structural thinking: you understand that the quality of an AI system's reasoning is largely a function of how well its knowledge is organized, and you can produce rigorous artifacts without waiting for perfect information - Comfortable operating in ambiguity: able to ask the right questions to reduce it, prioritize independently, and deliver structured outputs on deadlines in a fast-moving environment Preferred Qualifications: - Experience with enterprise B2B environments, professional services, or consulting is a plus Required Skills: Artificial intelligence, Knowledge engineering, Ontology, Semantic technologies, Knowledge representation, Ontology languages, modeling, OWL, RDF, SKOS, Knowledge graph construction, Semantic search, retrieval, LLM context window management, RAG architecture, AI agent design, orchestration, Structural thinking, Comfortable operating in ambiguity