Senior Product Manager – Semantic Search & AI (Patents and Technical Content)
Company: LexisNexis Legal & Professional
Location: Farringdon (Remote)
Type: Full-time
Remote: Yes
Posted: 2026-11-13
About this role
# Senior Product Manager – Semantic Search & AI (Patents and Technical Content)
LexisNexis Intellectual Property · London (hybrid)
## About us
LexisNexis Intellectual Property, part of RELX, helps the world's innovators, IP professionals, law firms and investors understand patents: their own, their competitors', and those of the companies they're assessing. Our products, including PatentSight+, IPlytics and TotalPatent One, and the patent data we deliver directly into customers' own systems, inform decisions on R&D investment, licensing, litigation, M&A and competitive strategy.
Behind them sits a global patent data platform, and on top of that data, a layer of intelligence: the capabilities that let people and AI systems find, understand and connect patents by meaning rather than by keyword. We're looking for the product manager who will lead it.
## Why this role is interesting
Patents are some of the most demanding documents there are to make machine-understandable. They're written in specialised legal and technical language, published in many languages, full of chemical structures, formulae and drawings, and their meaning often turns on a single phrase in a claim. Finding the one relevant document among many millions, or showing how technologies relate across companies and decades, takes far more than off-the-shelf search.
That's the problem you'll own. You'll decide how we use embeddings, semantic retrieval, clustering, translation and AI-assisted enrichment to turn a vast patent corpus into intelligence that our products, our customers and AI assistants can rely on. Frontier AI capabilities are moving fast; part of the job is judging which ones genuinely raise the bar for patent professionals, and making them real.
## What you'll do
- Own the product strategy and roadmap for the intelligence capabilities across our patent corpus, such as semantic search and retrieval, embeddings, technology clustering, machine translatio...