Jobs at LexisNexis

Build and own production-grade generative AI applications for legal technology, specializing in RAG, agentic systems, advanced search, embeddings, reranking, evaluation, and LLM workflows. Responsibilities include architecting modular Python applications, refactoring legacy code, implementing testing and observability, optimizing performance and costs, ensuring resilience and security, reviewing code, and supporting deployments and incident resolution.

Lead the design, refactoring, testing, deployment, and operational support of production-grade generative AI applications. Build agentic systems using retrieval, embeddings, reranking, LLMs, and advanced search. Improve reliability through resilient architecture, observability, validation, testing, monitoring, and incident response while optimizing latency, scalability, token usage, cost, and retrieval quality.

Implements pricing strategy for the Small Law Business Segment by responding to pricing inquiries, developing proposals, supporting deal approvals, and completing contract business terms. Analyzes pricing data, reconciles discrepancies, provides benchmarking and pricing guidance, supports renewals and upsells, addresses cost-recovery questions, and recommends pricing improvements to senior colleagues. The role collaborates with sales, segment, and legal teams and requires strong organization, communication, quantitative ability, and deadline management.

Leads the identification, development, integration, and global deployment of AI and automation solutions for legal editorial, metadata, and content operations. The role supports AI strategy, evaluates designs against governance and quality standards, manages cross-functional projects, reports data-driven outcomes, tracks industry trends, documents improvements, and promotes responsible AI use.

Lead CEMEA product strategy and cross-country transformation programs, aligning global and local product priorities. Manage planning, milestones, dependencies, risks, reporting, portfolio reviews, and organizational change. Drive AI adoption across product teams, including generative and agentic AI use cases, workflows, and skills. Analyze product data to support regional decisions and advise the VP Product through executive presentations, reporting, and priority coordination.

Lead design and validation of AI-driven legal product capabilities: develop NLP/LLM and generative AI solutions (RAG, prompts), design agentic workflows, build retrieval/hybrid search strategies with embeddings and vector DBs, analyze large legal datasets, establish model evaluation best practices, translate results into product recommendations, collaborate with product and engineering, and mentor junior team members.

Leads architecture, implementation, and scaling of production ML and LLM systems for legal products. Builds RAG pipelines, agentic applications, hybrid search, APIs, microservices, data pipelines, and model-serving infrastructure. Establishes reusable AI frameworks, deployment and observability practices, and CI/CD standards while optimizing latency, reliability, scalability, and cost. Partners with data scientists to productionize models and provides technical leadership in system design and engineering excellence.

Lead and mentor data scientists and analysts, develop predictive models and algorithms, conduct NLP and LLM experiments, design scalable data-driven solutions, and oversee statistical models and data architectures. Collaborate with cross-functional stakeholders to solve business problems, communicate actionable insights, and incorporate state-of-the-art data science methodologies while improving performance and reliability.

Resolve complex customer technical issues, implement tailored solutions, assess technical environments during pre-sales, and maintain relationships with key accounts. Collaborate with internal and external teams to troubleshoot and escalate issues, identify expansion opportunities, analyze trends, advocate for customers, and provide product improvement insights.

Designs, builds, and scales AI infrastructure and software supporting GenAI products. Responsibilities include managing model capacity, maintaining AI governance and security oversight, translating complex requirements into software designs, resolving complex technical issues, implementing coding best practices, conducting code reviews, and collaborating with and mentoring engineering and product teams.

Define positioning and messaging for SaaS and DaaS products; lead global go-to-market strategy and product launches; translate customer and market insights into commercial plans; support sales enablement and revenue growth; influence product strategy and collaborate with international teams.

Creates, develops, and maintains commercial legal practical guidance and current-awareness content. Monitors legal and market developments, produces news and analysis, engages with customers and legal professionals, supports practitioner queries, and collaborates across practice areas. The role requires an England and Wales-qualified lawyer with substantial commercial law experience, strong legal research and drafting skills, and the ability to communicate complex concepts clearly while meeting demanding deadlines.

Leads end-to-end development and production deployment of advanced AI and data science systems, including LLM, NLP, deep learning, RAG, and agent architectures. Designs scalable cloud pipelines, establishes model validation and governance practices, conducts experimentation, and monitors performance. Partners with product and business teams on risk, fraud, legal analytics, and compliance solutions; presents recommendations to leadership; mentors data scientists; and guides strategic data science initiatives.

Develop and validate agentic AI capabilities for patent analysis using machine learning, NLP, LLMs, RAG, hybrid search, and agentic workflows. Analyze large-scale intellectual property datasets, design experiments, evaluate and benchmark models, define reasoning strategies, and translate findings into product recommendations. Collaborate with product managers, IP experts, and engineers to deliver scalable, customer-facing solutions.

Lead sales effectiveness, operational improvement, and business transformation initiatives across APAC. Identify automation and efficiency opportunities, support product launches and customer adoption programs, establish KPIs, deliver performance insights, coordinate cross-functional governance, improve processes and workflows, and support business cases and ROI assessments. The role partners with Product, Commercial, Finance, Marketing, and Operations teams while driving AI-enabled transformation and strategic execution.

Reviews and analyzes contract data in English and Portuguese, performs quality and peer checks, ensures accuracy and compliance, responds to stakeholder requests, supports reporting and process improvements, and contributes to client service delivery in a remote environment.

Leads case law content operations across Pacific jurisdictions, ensuring editorial quality, accuracy, timeliness, service-level performance, and AI readiness. Manages workflows, operational metrics, process improvements, and relationships with courts, vendors, licensors, and content providers. Serves as the regional contact for case law operations and collaborates with product, technology, data science, editorial, and commercial teams to improve structured legal content and customer research experiences.

Leads teams responsible for expanding and maintaining caselaw content across LexisNexis platforms. Manages content quality, workflows, staffing, budgets, vendors, documentation, and business-as-usual delivery. Partners with Product, Technology, and commercial stakeholders to implement automation, Generative AI, process improvements, and global initiatives. Oversees metrics, change management, training, talent development, and senior leadership reporting while ensuring accurate, timely, and cost-effective digital and print content delivery.

Manages legal content workflows across Asia, ensuring metadata, taxonomy, XML/HTML structures, quality, currency, discoverability, and AI readiness. Coordinates editorial, product, technology, regional, and vendor stakeholders; supports publishing schedules, operational SLAs, workflow automation, testing, reporting, archival governance, and continuous improvement. Contributes to digital transformation, product enhancements, content expansion, benchmarking, and customer-focused improvements while resolving operational issues and maintaining content delivery standards.

Identify, engage, and qualify prospective business opportunities through targeted lists, creative multichannel outreach, lead follow-up, and conversations with senior decision makers. Generate qualified meetings for Enterprise Account Managers, provide detailed handovers, maintain accurate Salesforce records, deliver positive prospect experiences, and achieve weekly and monthly performance targets.