Remote AI Developer: Production LLM & RAG Pipelines

Brand & Bot; Chile; A distancia; CLP 89.021.000 - 128.586.000; A tiempo parcial

Descripción de la vacante

Brand & Bot is seeking an AI Developer to design and deploy production-grade LLM systems, including RAG pipelines, AI agents, and document intelligence. You will handle raw document ingestion, chunking, vector search, and tool-calling workflows, partnering with product and engineering teams to ship real systems.

You will work on end-to-end AI pipelines, optimize latency and cost, and contribute to observability, documentation, and best practices in a remote-first, contractor-engaged environment.

Formación

• 2-4 years of professional experience in AI, ML, or applied LLM development.
• Strong proficiency in Python and AI development workflows.
• Deep experience with LlamaIndex, LangChain, RAG architectures, and AI agents.
• Experience with vector databases and production AI deployments.
• Familiarity with AWS Bedrock and cloud-based services.

Responsabilidades

• Design and build LLM-based applications using modern AI frameworks (LlamaIndex, LangChain).
• Implement end-to-end RAG pipelines from data ingestion to retrieval and generation.
• Build and maintain vector-based retrieval systems using production databases like Qdrant, Pinecone, FAISS, Weaviate, and Chroma.
• Design and optimize document ingestion pipelines (PDFs, DOCX, complex layouts, tables).
• Define intelligent chunking strategies that preserve semantic context.
• Create metadata extraction and enrichment workflows.

Conocimientos

Python

LangChain

LlamaIndex

RAG architectures

Vector databases

AWS Bedrock

AI development workflows

Herramientas

HuggingFace Transformers

GitHub/GitLab

LangSmith

Qdrant

Pinecone

FAISS

Weaviate

Chroma

Descripción del empleo

Brand & Bot is seeking an AI Developer to design and deploy production-grade LLM systems, including RAG pipelines, AI agents, and document intelligence. You will handle raw document ingestion, chunking, vector search, and tool-calling workflows, partnering with product and engineering teams to ship real systems.

You will work on end-to-end AI pipelines, optimize latency and cost, and contribute to observability, documentation, and best practices in a remote-first, contractor-engaged environment.