Remote AI Engineer (Python) - RAG & LLM Systems

BairesDev

United States

Remote

MXN 2,238,000 - 3,358,000

Full time

26 hours ago
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Benefits offered by this job

Remote work
USD or local pay
Home office setup
Flexible hours
Parental leave

Job summary

BairesDev is seeking an AI Engineer (Python) to design and implement AI-powered systems using LLMs and RAG architectures. You will bridge AI research with production-ready applications, enabling intelligent automation across business workflows.

Responsibilities include building production-grade Python apps, designing RAG pipelines, integrating LLM APIs and vector databases, and ensuring scalable data processing for AI/ML pipelines. Comfortable with remote, global collaboration.

Qualifications

  • 4+ years of experience in AI Engineering, Software Engineering, or Data Science.
  • Described expertise in building AI-powered systems using LLMs.
  • Experience designing Retrieval-Augmented Generation (RAG) pipelines.

Responsibilities

  • Develop 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 to support complex reasoning and semantic search.
  • Architect scalable data processing systems for AI/ML content ingestions.
  • Collaborate with cross-functional teams to define AI strategy and opportunities for automation.
  • Monitor and refine model performance to ensure reliability, safety, and efficiency.

Skills

Python
LangChain
LLMs
RAG pipelines
AWS

Tools

AWS

Job description

BairesDev is seeking an AI Engineer (Python) to design and implement AI-powered systems using LLMs and RAG architectures. You will bridge AI research with production-ready applications, enabling intelligent automation across business workflows.

Responsibilities include building production-grade Python apps, designing RAG pipelines, integrating LLM APIs and vector databases, and ensuring scalable data processing for AI/ML pipelines. Comfortable with remote, global collaboration.

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