Jobs at RELX

Provide high-level administrative and project coordination support to VPs and reference content leadership. Manage calendars, meetings, travel, onboarding, contract and vendor workflows, org data, purchase orders, and cross-functional processes while supporting compliance, process improvements, and systems administration.

Submit and manage state notice filings for mutual funds and investment products using BSS; perform renewals, amendments and special filings under manager supervision; maintain fund files, liaise with state examiners, ensure compliance with policies, and participate in electronic filing testing and process improvements.

Senior, consultative, client-facing role partnering with account managers to drive expansion of AI solutions at law firms. Build relationships with firm leadership, conduct senior-level discovery and workflow analysis, design tailored demos and proofs-of-concept, and influence product and post-sales adoption to deliver measurable ROI and revenue growth.

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.

Lead go-to-market strategy, positioning, and messaging for AI-enabled research solutions. Develop value propositions, launch plans, sales enablement materials, competitive analysis, and cross-functional alignment to drive adoption and revenue among institutional buyers, researchers, funders, and publishers.

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.

Lead design and implementation of large-scale search and retrieval systems, improve relevance using lexical and vector techniques, build scalable data workflows and microservices with Spark and Airflow, write production-quality code in Python/Java/Scala, diagnose distributed system issues, mentor engineers, and collaborate cross-functionally to deliver a shared search platform and developer-facing tooling.

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.

Lead customer-facing technical integrations for SaaS fraud and identity solutions. Design, test, deploy, and optimize mobile SDKs, web fingerprinting, and REST API integrations. Advise developers and business stakeholders, present findings, troubleshoot implementations, and support adoption. Occasional travel required.

Design, build, and optimize generative AI, RAG, and agentic RAG systems for drafting, search, and reasoning. Improve LLM outputs via prompt design, retrieval optimization, embeddings, reranking, and evaluation. Develop production-grade ML components and retrieval pipelines using OpenSearch/Solr, write maintainable Python code, and collaborate with engineering, product, and domain teams to improve relevance, accuracy, and user trust.

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 technical design and delivery of scalable search and retrieval systems. Provide hands-on coding in Python/Java, guide architecture and platform decisions, mentor engineers, implement vector and lexical search (Elasticsearch/Lucene/Solr), integrate AI/LLM features, and ensure observability, performance, and cross-team alignment.

Lead product management enablement and operations for Clinical Solutions: build training, playbooks, and tooling governance; improve roadmap quality and PM processes; track health metrics and dashboards; coordinate leadership forums; and drive cross-functional alignment to improve consistency and execution.

Serve as a strategic, consultative Customer Success Manager for large law firm accounts, driving adoption of LexisNexis drafting, research, analytics, and AI workflows. Build trusted advisor relationships, create success plans, lead change management, use data to monitor health and identify growth or churn risks, and partner cross-functionally to improve products and retention.

Design, deploy, and maintain highly available Kubernetes clusters on AWS EKS; manage and optimize cloud infrastructure; develop IaC and automation; implement CI/CD (GitHub Actions); monitor multi-region systems, troubleshoot incidents, perform root cause analysis; document best practices; and mentor junior engineers.