Remote AI Engineer (Python) — Build Scalable LLM Solutions

BairesDev; Chile; Remote; CLP 117,417,000 - 176,125,000; Full time

Benefits offered by this job

100% remote work

USD or local currency pay

Hardware provided

Flexible hours

Parental leave

Paid vacations & holidays

Mentorship & growth opportunities

Global team

Job summary

BairesDev is seeking an AI Engineer (Python) to design and implement AI-powered systems leveraging Large Language Models (LLMs) and RAG architectures. You will act as a key link between cutting-edge AI research and production-ready applications, ensuring intelligent automation is integrated into business workflows.

You will develop production-grade AI applications with Python, design and deploy RAG pipelines, integrate LLM APIs and vector databases, and collaborate with cross-functional teams to

Qualifications

• 4+ years of experience in AI/Software/Data Science fields.
• Proven expertise in building AI-powered systems with LLMs.
• Experience designing and implementing Retrieval-Augmented Generation (RAG) pipelines.
• Python proficiency and familiarity with LangChain/AI frameworks.
• Experience integrating LLM APIs and cloud services (AWS).
• Strong English communication skills.

Responsibilities

• Develop and maintain production-grade AI applications using Python and LangChain.
• Design and implement RAG pipelines to improve model accuracy with external data.
• Integrate LLM APIs and vector databases for semantic search and reasoning.
• Architect scalable data processing for AI/ML workflows.
• Collaborate with cross-functional teams to shape AI strategy and automation.

Job description

BairesDev is seeking an AI Engineer (Python) to design and implement AI-powered systems leveraging Large Language Models (LLMs) and RAG architectures. You will act as a key link between cutting-edge AI research and production-ready applications, ensuring intelligent automation is integrated into business workflows.

You will develop production-grade AI applications with Python, design and deploy RAG pipelines, integrate LLM APIs and vector databases, and collaborate with cross-functional teams to