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 translation and AI-assisted enrichment
• Work closely with data scientists, engineers, architects and patent subject matter experts to decide what to build, how quality will be measured, and when it is good enough to ship
• Set the KPIs that show whether these capabilities are succeeding, from technical quality (such as relevance and coverage) through to their impact on products, customers and the business, and report progress against them
• Champion evaluation-driven development: define how relevance and quality are tested, using query sets, expert judgments and automated evaluation, and use the results to guide priorities
• Track the state of the art in AI and retrieval, benchmark our capabilities against it, make clear-eyed build, buy or partner recommendations, and build the business case for investment
• Coordinate cross-team programmes that span several engineering teams, keeping plans, dependencies and progress visible
• Build close relationships with customers and with the product teams that build on these capabilities, and use them to shape direction; represent the capabilities to senior stakeholders

What you'll bring

• Substantial product management experience, including ownership of AI, machine learning, search or information retrieval products in production, over multiple releases
• Hands-on understanding of modern AI and retrieval: embeddings, vector and hybrid search, LLMs and retrieval-augmented generation, and their failure modes
• Experience defining and using evaluation methods for AI or search quality (for example relevance metrics, labelled test sets, LLM-based evaluation or online experiments) to make product decisions
• Strong technical depth: you can explore data and prototypes yourself (for example in Python or SQL) and hold your own in design discussions with data scientists and engineers
• You work in an AI-first way: you use AI assistants and agents day to day to analyse data, build quick prototypes and visualisations, and draft and test ideas (for example AI coding and analysis assistants, notebook-based data platforms, and AI-enabled prototyping or design tools)
• A record of setting KPIs that link technical quality to customer and business outcomes, and of driving complex work across multiple teams to deliver against them, mentoring others along the way
• The ability to turn technical possibilities into customer value, and to explain trade-offs to technical and non-technical audiences alike
• A love of hard, ambiguous problems and the curiosity to learn a demanding domain in depth

Experience and education

• Typically 8 or more years in product management or closely related roles
• A degree in computer science, engineering, a scientific subject or a related field, or equivalent practical experience; a master's degree is a plus

It would be great if you also have

• Experience with patent, legal, scientific or other professional or technical content
• Experience with multilingual search, machine translation or non-text content such as chemical structures or images
• Familiarity with knowledge graphs, entity resolution or semantic data modelling

You don't need to have worked with patents before. We'll help you learn the domain; you bring the depth in AI and retrieval.

This role is probably not for you if you're mainly interested in user-interface features, or in building thin wrappers around a general-purpose AI model. This role is about the intelligence those experiences depend on.

Why join us

You'll work at the point where trusted, expert-curated content meets fast-moving AI, with the backing of a global group that has been building data, analytics and AI products for many years, and with colleagues who care deeply about getting answers right.

In your application

Please tell us briefly about a time you improved the quality of an AI or search capability, for example semantic search, embeddings, ranking, or retrieval for an AI assistant: how you measured it, what you changed, what difference it made to users and, if relevant, how you used AI tools in your own work along the way.

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