Jobs at RELX

Develops, licenses, and manages analytical tax, accounting, and legal content for professional customers. Responsibilities include researching tax law, legislation, regulations, and case law; writing and editing practical guidance; using generative AI to improve content workflows; recruiting authors and negotiating licensing agreements; and collaborating with editorial, product, technical, sales, and marketing teams. Requires a JD, CPA designation, significant accounting experience, and at least two years each of tax legal and accounting experience.

Corporate Counsel provides independent legal advice across multiple disciplines, interprets laws and policies, resolves complex issues, drafts policies and documentation, and develops legal templates, playbooks, and best practices. The role serves as a strategic business partner and subject matter expert, communicates legal risks clearly, supports stakeholder decision-making, and contributes to functional strategy and compliance.

Build and productionize AI-powered features, including RAG pipelines, tool-augmented agents, and agentic workflows. Integrate AI capabilities into enterprise systems, contribute to evaluation, observability, guardrails, and outcome measurement, and maintain reusable, high-quality code. Work autonomously with stakeholders to ensure solutions fit real workflows, identify technical risks, and support handover and capability-building after delivery.

Drive adoption and retention of Healthcare customers by qualifying opportunities, architecting solutions, aligning stakeholders, delivering sales pitches, and providing post-sales support. Partner with Sales and cross-functional teams to tailor LexisNexis healthcare solutions, run training/workshops, analyze market trends, and support client deployments. Travel up to 35%.

Designs, develops, and supports scalable Salesforce Sales Cloud solutions for sales, operations, and customer success teams. Responsibilities include Apex, LWC, Flow, integrations, customer data management, AI-driven automation, CI/CD, release management, production troubleshooting, and technical leadership. The role requires deep Sales Cloud expertise, API integration experience, Copado, Git, SFDX, and advanced Salesforce automation skills.

Leads cross-functional process standardization initiatives across Client Services. Responsibilities include mapping current processes, creating SOPs and knowledgebase content, managing project plans and milestones, coordinating stakeholders, assessing automation readiness, measuring KPI improvements, and driving adoption of standardized workflows.

Leads security compliance for a FedRAMP-authorized cloud environment. Maintains the ATO, coordinates continuous monitoring, assessments, audits, penetration testing, risk reviews, POA&M remediation, security documentation, and NIST control implementation. Partners with engineering, DevOps, cloud operations, compliance, and government stakeholders to support incident response, secure system changes, cloud deployments, and audit readiness.

Build and operate reliable, scalable platforms and services across AWS environments. Responsibilities include infrastructure automation with Terraform, CI/CD development, observability, incident response, disaster recovery testing, AI service deployment, security, infrastructure documentation, and developer enablement. The role partners with engineering teams to improve availability, performance, recovery, and operational self-service.

Design, develop, and deploy ML, NLP, and generative AI solutions to improve scientific discovery. Build retrieval, recommendation, ranking, and RAG systems; fine-tune and evaluate LLMs; create evaluation frameworks; build scalable data pipelines; collaborate with cross-functional teams and produce production-quality Python code to deliver reliable, impactful AI systems for research use.

Design, build, evaluate, and scale production-ready AI solutions (LLMs, NLP, retrieval, RAG, knowledge graphs) to support scientific discovery. Lead architecture, mentor data scientists, partner with engineering and product, and measure model quality, trustworthiness, and user impact.

Lead and develop data science teams to deliver AI/ML, NLP, search, retrieval, and generative AI products for scientific discovery. Set strategy, ensure model quality and responsible AI, partner with product and engineering, mentor staff, and drive measurable impact from research to production.

Senior MLOps engineer to productionize NLP/GenAI models and RAG systems: build and automate ML pipelines, CI/CD, model registries, search/vector/graph-based retrieval, evaluation metrics and cost-optimized scalable infrastructure, collaborating with data scientists, product and operations teams.