AI Architect

LexisNexis

AI Architect responsible for managing AI architecture vision and decisions at LexisNexis. Collaborating across teams to ensure system coherence, security, and compliance.

Posted 7/22/2026full-timeFarringdon • 🇬🇧 United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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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.

Highest-signal resume keywords

AI Architecture VisionPython ProficiencyLLM-Based Systems DeliveryEvent-Driven Architecture DesignResponsible AI Principles Knowledge

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Applicant Tracking System Keywords

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Hard Skills

AI/ML ArchitectureSoftware EngineeringProduction LLM SystemsVector DatabasesSemantic Search Pipeline DesignModel Context Protocol (MCP)Cloud-Native ArchitecturesKafkaData Privacy CompliancePatent Data Structures

Soft Skills

CommunicationCollaborationTechnical Decision-Making

Tools & Technologies

DatabricksElasticsearchMicroservicesArchitecture Decision Records (ADRs)

Certifications & Qualifications

Advanced Degree in Computer ScienceAdvanced Degree in Artificial IntelligenceAdvanced Degree in Data Science

Industry Keywords

Intellectual PropertyLegal TechnologyScientific InformationAI Risk AssessmentRegulatory Compliance

Tech Stack

Tools & technologies

CloudElasticSearchKafkaPython

About the role

Key responsibilities & impact

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

What you’ll need

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.

Benefits

Comp & perks

Generous holiday allowance with the option to buy additional days.
Health screening, eye care vouchers, and private medical benefits
Wellbeing programs
Life assurance
Access to a competitive contributory pension scheme
Save As You Earn share option scheme.
Travel Season ticket loan.
Electric Vehicle Scheme
Optional Dental Insurance
Maternity, paternity, and shared parental leave
Employee Assistance Programme
Access to emergency care for both the elderly and children
RECARES days, giving you time to support the charities and causes that matter to you.
Access to employee resource groups with dedicated time to volunteer.
Access to extensive learning and development resources
Access to employee discounts scheme via Perks at Work