RAG AI Engineer: Grounded LLMs & Knowledge Pipelines

BairesDev; Colombia; Presencial; COP 286.250.000 - 413.473.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

100% remote

USD or local currency compensation

Hardware provided

Flexible hours

Paid holidays

Global multicultural environment

Mentorship and growth opportunities

Descripción de la vacante

BairesDev is seeking an AI Engineer (RAG) to design and implement retrieval-augmented generation systems, grounding responses to external knowledge bases and reducing hallucinations.

You will build end-to-end RAG pipelines, manage vector databases, and collaborate with global teams to deploy enterprise-grade AI solutions. The role requires 4+ years in AI/ML or software engineering and strong Python plus English proficiency.

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

Python

RAG architectures

Embeddings

Chunking strategies

English (Advanced)

Vector databases

Herramientas

Pinecone

Qdrant

Weaviate

Descripción del empleo

BairesDev is seeking an AI Engineer (RAG) to design and implement retrieval-augmented generation systems, grounding responses to external knowledge bases and reducing hallucinations.

You will build end-to-end RAG pipelines, manage vector databases, and collaborate with global teams to deploy enterprise-grade AI solutions. The role requires 4+ years in AI/ML or software engineering and strong Python plus English proficiency.