Remote AI Search Engineer, RAG & Vector Systems

BairesDev; Comisión de Fomento de Perú; A distancia; ARS 185.819.000 - 278.728.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Remote work

Competitive USD pay

Home office setup

Flexible hours

Parental leave

Growth opportunities

Descripción de la vacante

BairesDev is seeking a Search Engineer (AI) to design and implement advanced retrieval systems for AI applications. You will translate complex user intent into efficient search architectures and ensure RAG systems deliver relevant information at scale.

Join a fully remote, globally distributed team working with top-tier partners; you will collaborate with AI teams, optimize vector databases, embeddings, and reranking strategies to maintain production-grade reliability.

Formación

• 4+ years of experience in Software Engineering, AI Engineering, or Data Engineering.
• Proven expertise in building and optimizing retrieval-augmented generation (RAG) pipelines.
• Proficiency in Python and vector databases like Pinecone, Qdrant, or Weaviate.
• Hands-on experience with embedding techniques, chunking strategies, and reranking algorithms.
• Familiarity with RAG evaluation frameworks such as RAGAS to ensure system performance.
• Advanced proficiency in English.

Responsabilidades

• Design and design vector database architectures for semantic search.
• Develop and optimize retrieval-augmented generation (RAG) pipelines.
• Implement reranking techniques (ColBERT, Reciprocal Rank Fusion) to improve precision.
• Build and maintain hybrid search solutions combining keyword and vector retrieval.
• Evaluate search performance using frameworks like RAGAS for production reliability.
• Collaborate with AI teams to integrate search components into broader workflows.

Conocimientos

RAG pipelines

Python

Vector databases

Embeddings

Re-ranking

English

Herramientas

Pinecone

Qdrant

Weaviate

RAGAS

Descripción del empleo

BairesDev is seeking a Search Engineer (AI) to design and implement advanced retrieval systems for AI applications. You will translate complex user intent into efficient search architectures and ensure RAG systems deliver relevant information at scale.

Join a fully remote, globally distributed team working with top-tier partners; you will collaborate with AI teams, optimize vector databases, embeddings, and reranking strategies to maintain production-grade reliability.