Remote AI Engineer (RAG) & Semantic Search

BairesDev; Comisión de Fomento de Perú; Remote; ARS 185,819,000 - 278,728,000; Full time

Benefits offered by this job

Remote work

USD/local currency pay

Home office setup

Flexible hours

Parental leave & holidays

Multicultural environment

Mentorship & growth

Job summary

BairesDev is seeking an AI Engineer specialized in RAG to design and implement advanced retrieval-augmented generation systems that ground responses in factual, domain-specific data and connect external knowledge bases to enterprise-grade applications.

You will build end-to-end RAG pipelines, manage vector databases, develop chunking and reranking strategies, evaluate performance with established frameworks, and collaborate with data and software teams to deliver scalable, production-ready

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.

Responsibilities

• Design and optimize end-to-end RAG pipelines, including ingestion, cleaning, chunking, and embedding workflows.

Skills

RAG architectures

Hybrid search

Python

Embeddings & chunking

English proficiency

Tools

Pinecone

Qdrant

Weaviate

Job description

BairesDev is seeking an AI Engineer specialized in RAG to design and implement advanced retrieval-augmented generation systems that ground responses in factual, domain-specific data and connect external knowledge bases to enterprise-grade applications.

You will build end-to-end RAG pipelines, manage vector databases, develop chunking and reranking strategies, evaluate performance with established frameworks, and collaborate with data and software teams to deliver scalable, production-ready