Head of Ontology - Platform

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Growth AI Performance System is Bain’s integrated suite of agentic decisioning tools giving large organizations always‑on intelligence across their most important growth decisions. It sits at a rare intersection few organizations can genuinely offer: the analytical depth and client access of a top‑tier consultancy, the technical ambition of a product company, and the commercial stakes of both.

You will own the knowledge and data layer behind Bain’s persistent product team, building software that helps Fortune 100 to 500 companies answer the questions that drive their business: where to invest, where to focus, and how to win. The impact of what you build is direct and immediate, and the suite compounds in value with every release.

The platform has two layers working together: the Agentic Core and three product modules, each solving a distinct commercial problem. Your job is to ensure the knowledge layer underneath every module — the entities, relationships, and taxonomies the platform reasons over — is engineered with the same production rigor as the pipelines and models built on top of it.

This is a startup inside an established company. You get genuine early‑stage ownership -- real influence over architecture and product direction -- backed by Bain’s global scale, client relationships, and leadership commitment. The pace of a startup with the runway of a global firm.

We are looking for someone who sits genuinely at the intersection of data engineering and AI engineering — comfortable owning large‑scale entity resolution and pipeline infrastructure one day, and the retrieval, embedding, and agent‑facing API contracts that let that knowledge power live reasoning the next. This is applied knowledge engineering in production, at scale, with real users depending on what you build.

Native AI fluency matters here, and so does the drive to keep learning -- because the field is moving fast and this team is built to move with it.

The Head of Ontology is the most senior knowledge engineering role in Growth AI Performance System and one of the most strategically important. You own the knowledge and ontology standard for every Growth AI Performance System product module. You sit above module‑level AI Engineers and Data Engineers on questions of entity resolution, taxonomy, and knowledge architecture — and you are the final word when a modeling or retrieval question depends on how the platform represents the commercial world.

You are expected to personally build the hardest parts of this layer, not only set direction for others.

The problems span entity resolution at scale, knowledge graph and taxonomy design, retrieval and embedding architecture, and the data pipelines that keep all of it fresh and correct — hard engineering problems where a wrong call quietly propagates into every downstream model and agent. You must be equally credible reviewing a Spark pipeline and a retrieval‑augmented generation architecture, because both are your responsibility.

You will work across the platform and…