AI Architect

Jobtailor

Farringdon

On-site

GBP 140,000 - 180,000

Full time

14 days+

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Job summary

RELX seeks an AI Architecture leader to define and own the Protégé AI vision within PatentSight+. You will evaluate technologies, author ADRs, and design scalable, auditable AI systems combining structured analytics with unstructured data across multiple sources.

You will orchestrate agentic reasoning, RAG pipelines, and knowledge integration while ensuring security, privacy, and regulatory compliance in a cloud-native, event-driven environment.

Qualifications

Experience in AI/ML architecture and production LLM systems.
Proven track record delivering LLM-based solutions with RAG pipelines.
Strong Python skills; enterprise integration with C# or similar.
Hands-on with vector databases and semantic search pipelines.
Experience with MCP and cloud-native event-driven architectures.

Responsibilities

Define and own the AI architecture vision for Protégé within PatentSight+.
Evaluate AI technologies and platform components to align with product strategy.
Author Architecture Decision Records and system design docs.
Collaborate with Product, Security, and Platform teams on enterprise requirements.

Skills

AI Architecture Vision

Production LLM Systems

Python

Vector Databases

Semantic Search

MCP

Cloud-Native

Kafka

Data Privacy

Technical Documentation

Education

Advanced Degree in Computer Science

Advanced Degree in Artificial Intelligence

Advanced Degree in Data Science

Tools

Databricks

Elasticsearch

ADR s

Job description

Define and own the AI architecture vision for Protégé in PatentSight+, 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.

Requirements

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 governance, and observability.
Experience communicating complex architectural decisions through written documents, diagrams, and presentations to diverse audiences.
Background in the intellectual property, legal technology, or scientific information domain; familiarity with patent data structures and classification systems.
Knowledge of Responsible AI Principles.
Advanced degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
Experience designing event-driven, cloud-native architectures using Kafka (or equivalent streaming platforms), including topic design, schema governance, and consumer patterns.

Core Competencies

Demonstrates expertise in AI architecture, focusing on the design and implementation of large-scale AI systems, including LLM-based solutions and compliance with Responsible AI Principles. Proficient in translating complex technical requirements into actionable architectural strategies while ensuring security, privacy, and reliability.

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