Senior RAG AI Engineer — Flexible Hours, Legal Tech

LexisNexis Risk Solutions; México; Vor Ort; MXN 700.000 - 1.000.000; Vollzeit

Benefits dieser Stelle

Flexible hours

Parental leave

Study assistance

Sabbaticals

Zusammenfassung

LexisNexis Legal & Professional is seeking an AI Engineer focused on Retrieval-Augmented Generation to design, build, and optimize RAG applications for source-grounded, trustworthy information in legal and professional tech.

You will work with vector databases like Qdrant, Pinecone, or OpenSearch vector search, develop ingestion and embedding workflows, and collaborate across teams to improve response quality while reducing hallucinations.

Qualifikationen

• Hands-on experience with Retrieval-Augmented Generation (RAG) applications, including document ingestion, chunking, embedding generation, retrieval, reranking, and source-grounded responses.
• Strong understanding of Generative AI and LLM capabilities, limitations, hallucination mitigation, and response-quality evaluation.
• Experience designing and operating vector search solutions using Qdrant, Pinecone, pgvector, LanceDB, OpenSearch vector search, or equivalent technologies.

Aufgaben

• Design, build, and optimize Retrieval-Augmented Generation (RAG) applications.
• Develop and manage document ingestion, chunking, embedding generation, retrieval, reranking, and source-grounded response workflows.
• Design and operate vector search solutions using modern vector databases.
• Validate retrieval quality, citation accuracy, relevance, coverage, and factual grounding using reproducible evaluation 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 techniques.
• Monitor and evaluate retrieval performance, latency, cost, and AI system quality.
• Support the development of scalable and responsible Generative AI solutions across legal and professional information products.

Kenntnisse

RAG applications

Generative AI concepts

Evaluation datasets

Latency monitoring

Ausbildung

Advanced degree in CS/ML

Tools

Qdrant

Pinecone

pgvector

LanceDB

OpenSearch vector search

Jobbeschreibung

LexisNexis Legal & Professional is seeking an AI Engineer focused on Retrieval-Augmented Generation to design, build, and optimize RAG applications for source-grounded, trustworthy information in legal and professional tech.

You will work with vector databases like Qdrant, Pinecone, or OpenSearch vector search, develop ingestion and embedding workflows, and collaborate across teams to improve response quality while reducing hallucinations.