RAG AI Engineer - Remote, Flexible Hours, Grounded GenAI

BairesDev; Comisión de Fomento de Perú; À distance; ARS 185 819 000 - 278 728 000; Plein temps

Avantages offerts par ce poste

100% remote work (from anywhere)

Excellent compensation in USD or your

Hardware and software setup for you to

Flexible hours: create your own

Paid parental leaves, vacations, and

Innovative and multicultural work env.

Mentorship and growth opportunities

Résumé du poste

BairesDev is seeking an experienced AI Engineer specializing in Retrieval-Augmented Generation (RAG) to design and implement end-to-end RAG pipelines and integrate with external knowledge bases. You will work remotely on enterprise-grade projects, delivering grounded, high-quality responses while minimizing hallucinations.

You will collaborate with data and software teams, optimize vector databases, experiment with chunking and reranking, and evaluate performance using established frameworks.

Qualifications

• 4+ years of experience in AI Engineering, Machine Learning, or Software Engineering.
• Proven expertise in implementing Retrieval-Augmented Generation (RAG) architectures and hybrid search.
• Advanced proficiency in Python and working with vector databases like Pinecone, Qdrant, or Weaviate.
• Hands-on experience with chunking strategies, embeddings, and reranking techniques.
• Familiarity with evaluation frameworks such as RAGAS to ensure model performance and groundedness.
• Advanced proficiency in English.

Responsabilités

• Design and optimize end-to-end RAG pipelines, including ingestion, cleaning, chunking, and embedding workflows.
• Implement and manage high-performance vector databases to enable efficient semantic and hybrid search.
• Develop sophisticated chunking and reranking strategies to improve the precision and contextual relevance of retrieved information.
• Evaluate and benchmark RAG system performance using established frameworks to ensure high-quality, production-ready outputs.
• Collaborate with data and software teams to integrate RAG capabilities into enterprise-grade applications and workflows.
• Research and apply emerging techniques in retrieval-augmented generation, such as agentic RAG and context compression.

Connaissances

Python

RAG

Embeddings

Reranking

English

Outils

Pinecone

Qdrant

Weaviate

Description du poste

BairesDev is seeking an experienced AI Engineer specializing in Retrieval-Augmented Generation (RAG) to design and implement end-to-end RAG pipelines and integrate with external knowledge bases. You will work remotely on enterprise-grade projects, delivering grounded, high-quality responses while minimizing hallucinations.

You will collaborate with data and software teams, optimize vector databases, experiment with chunking and reranking, and evaluate performance using established frameworks.