Senior RAG ML Engineer - Retrieval & Vector Search

LexisNexis; Ciudad de México; Presencial; MXN 600.000 - 900.000; Jornada completa

Descripción de la vacante

LexisNexis Legal & Professional is seeking an AI Engineer specialized in Retrieval-Augmented Generation (RAG) to design, build, and optimize AI-powered experiences with source-grounded results.

You will work on retrieval systems, evaluation frameworks, and cross-functional collaboration to ensure accurate, trustworthy information while advancing responsible AI practices across legal and professional information products.

Formación

• Hands-on experience with Retrieval-Augmented Generation (RAG) applications, including ingestion, chunking, embedding, retrieval, and source-grounded responses.
• Strong understanding of Generative AI, LLM capabilities, and strategies to mitigate hallucinations.
• Experience designing and operating vector search solutions with Qdrant, Pinecone, pgvector, LanceDB, or OpenSearch vector search.
• Ability to validate retrieval quality, citation accuracy, relevance, coverage, and factual grounding.

Responsabilidades

• Design, build, and optimize Retrieval-Augmented Generation (RAG) applications.
• Develop document ingestion, chunking, embedding generation, retrieval, reranking, and source-grounded workflows.
• Design and operate vector search solutions using modern vector databases.
• Validate retrieval quality and citation accuracy with reproducible datasets.
• Collaborate with cross-functional teams to improve response quality and reduce hallucinations.
• Implement hybrid search strategies combining keyword, metadata, semantic/vector search, and reranking.
• Monitor retrieval performance, latency, cost, and AI system quality.
• Support scalable, responsible Generative AI across legal and professional information products.

Conocimientos

RAG applications

LLM capabilities

Evaluation datasets

Vector search

Herramientas

Qdrant

Pinecone

pgvector

LanceDB

OpenSearch

Descripción del empleo

LexisNexis Legal & Professional is seeking an AI Engineer specialized in Retrieval-Augmented Generation (RAG) to design, build, and optimize AI-powered experiences with source-grounded results.

You will work on retrieval systems, evaluation frameworks, and cross-functional collaboration to ensure accurate, trustworthy information while advancing responsible AI practices across legal and professional information products.