AI Architect

AI Architect

Excited to uncover insights from complex data and turn them into impactful business decisions?

Do you enjoy building predictive models, experimenting with advanced analytics, and solving real-world challenges with data?

Lexis Nexis Intellectual Property Solutions (LNIP) is the global leader in patent intelligence, bringing clarity to innovation for businesses, law firms, universities, and government agencies worldwide. Our mission is to help the innovation community make better decisions faster, with greater confidence, combining the world’s most trusted patent data with sophisticated analytics, AI-powered insights, and purpose-built workflows.

Protégé in Patent Sight is LNIP’s next‑generation agentic AI assistant, purpose‑built for strategic patent analysis. Protégé replaces complex filter‑based workflows with natural language questions, surfacing structured, decision‑ready insights grounded in trusted data and established metrics.

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

This is a senior individual‑contributor role with broad influence. You will partner closely with Engineering Leads, Product Managers, Data Scientists, and data teams within LNIP.

• Define and own the AI architecture vision for Protégé in Patent Sight+, ensuring technical decisions are coherent, future‑proof, and aligned with product strategy.
• Evaluate and recommend AI technologies, modelling approaches, and platform components.
• Stay up to date with advances in agentic AI and domain‑specific AI research. Translate emerging capabilities into practical architectural recommendations.
• Author and maintain Architecture Decision Records (ADRs) and system design documentation, providing a clear and durable record of technical choices and their rationale.
• Architect the agentic reasoning systems that enable Protégé to decompose complex patent questions, plan multi‑step analyses, and compose insights from multiple data sources.
• Design retrieval and search architectures that deliver accurate, low‑latency patent intelligence across both structured analytics and unstructured text corpora.
• Define patterns for AI‑driven enrichment and classification of patent data at scale, ensuring results are dependable, auditable, and consistent with established IP metrics.
• Establish prompt engineering standards, evaluation harnesses, and quality frameworks to govern LLM behaviour and maintain output accuracy in production.
• Partner with Product Management to assess technical feasibility and shape the AI roadmap, translating product goals into deliverable system designs.
• Collaborate with Security and Platform teams to ensure AI systems meet enterprise requirements for access control, data privacy, and regulatory compliance.
• Ensure all AI systems comply with RELX Responsible AI Principles.
• Lead AI risk assessment activities, contributing to compliance with applicable regulatory frameworks.
• Communicate complex architectural decisions clearly to senior leadership, engineering teams, and non‑technical stakeholders.

• Strong professional software engineering expertise, with experience in a dedicated AI/ML architecture, principal engineer, or distinguished engineer role.
• Proven track record delivering production LLM‑based systems, including RAG pipelines, agentic/tool‑use frameworks, and multi‑step reasoning workflows.
• Strong proficiency in Python for AI service development; working knowledge of C# or equivalent compiled language for enterprise microservice integration.
• Hands‑on experience with vector databases and semantic search pipeline design.
• Experience with Model Context Protocol (MCP).
• Experience with large‑scale data platforms such as Databricks, and search engines such as Elasticsearch, in an analytical or AI feature engineering context.
• Demonstrated ability to design enterprise‑grade AI systems with strong non‑functional requirements: security, privacy, reliability, cost…