AI Architect – Lead AI Systems for Patent Intelligence

About the role

As an AI Architect you will be the technical authority for the AI systems that power Protégé within PatentSight+. You will work across the full stack, from the agentic reasoning layer down to retrieval and search components, ensuring every layer is coherent, scalable, secure, and aligned with RELX Responsible AI standards.

Key responsibilities

• Define and own the AI architecture vision for Protégé, aligning technical decisions with product strategy.
• Evaluate, recommend, and integrate AI technologies, modelling approaches, and platform components.
• Stay current with advances in agentic AI and domain‑specific research, translating them into practical architectural recommendations.
• Author and maintain Architecture Decision Records (ADRs) and system design documentation.
• Design agentic reasoning systems that decompose complex patent questions, plan multi‑step analyses, and synthesize insights from multiple data sources.
• Architect retrieval and search solutions that deliver accurate, low‑latency patent intelligence across structured and unstructured corpora.
• Define patterns for AI‑driven enrichment and classification of patent data at scale, ensuring dependability and auditability.
• Establish prompt‑engineering standards, evaluation harnesses, and quality frameworks to govern LLM behaviour in production.
• Partner with product management to assess technical feasibility and shape the AI roadmap.
• Collaborate with security and platform teams to ensure AI systems meet compliance and reliability requirements.

Required profile

• Senior individual‑contributor with broad influence across engineering, product, and data teams.
• Proven experience designing end‑to‑end AI systems for complex, data‑intensive domains.
• Strong understanding of Responsible AI principles and ability to embed them in architecture.
• Excellent communication skills to articulate technical decisions to cross‑functional stakeholders.

Required skills

• Agentic AI design
• Large Language Models (LLM) integration
• Prompt engineering
• Retrieval and search architecture
• AI‑driven data enrichment
• Scalable classification pipelines
• Responsible AI standards implementation