AI Context and Ontology Development Intern

🕒 May 1

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Marketbridge

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 1991

🤝 B2B

💰 Private Equity Round on 2023-11

B2B • Marketing & Communications • Technology

Marketbridge is a growth consulting and marketing firm that combines management consultancy with marketing agency capabilities. They specialize in go-to-market consulting, growth strategy, and operational optimization, utilizing marketing science, analytics, and technology to drive sustainable revenue growth for clients across various industries. Their services include audience insights, brand messaging, demand generation, and digital experiences, all aimed at helping modern leaders transform their market presence and optimize marketing effectiveness.

📋 Description

• 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.

🎯 Requirements

• 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. • Experience with enterprise B2B environments, professional services, or consulting is a plus. What matters most is the ability to operate at the intersection of conceptual rigor and practical delivery.

🏖️ Benefits

• Hands-on experience • Learning opportunities