Senior Data Scientist: LLMs, RAG & Agentic AI

LexisNexis Legal & Professional group; United States; Sur place; MXN 450 000 - 750 000; Plein temps

Résumé du poste

LexisNexis Legal & Professional is seeking a Senior II Data Scientist to lead AI initiatives using LLMs, Retrieval-Augmented Generation (RAG), and agentic workflows. You will work closely with product managers, domain experts, and stakeholders to translate business needs into scalable, production-ready solutions.

You will design end-to-end AI architectures, monitor performance, and contribute to software development as an individual contributor.

Qualifications

• 2 to 5 years of hands-on Data Scientist experience.
• At least 1 year building RAG-based applications and agentic AI systems.
• Ability to design end-to-end AI solution architectures with ingestion, retrieval, generation, and evaluation components.
• Strong proficiency in Python and modern AI frameworks; production-grade software practices.

Responsabilités

• Lead end-to-end AI projects using LLMs, RAG, and agentic workflows from problem definition to deployment.
• Monitor and optimize AI system performance using metrics and experimentation.
• Collaborate with Product and stakeholders to translate business needs into scalable AI solutions.
• Contribute to software development as an individual contributor.
• Design scalable AI architectures for data ingestion, retrieval, generation, and evaluation.

Connaissances

Data science

English communication

Problem solving

Team collaboration

Outils

Python

LangChain

Google ADK

Cloud platforms

Vector search

Description du poste

LexisNexis Legal & Professional is seeking a Senior II Data Scientist to lead AI initiatives using LLMs, Retrieval-Augmented Generation (RAG), and agentic workflows. You will work closely with product managers, domain experts, and stakeholders to translate business needs into scalable, production-ready solutions.

You will design end-to-end AI architectures, monitor performance, and contribute to software development as an individual contributor.