Teams 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.