Remote AI Engineer: Build AI Features & RAG Pipelines

BairesDev; United States; Remote; MXN 1,292,000 - 2,215,000; Full time

Benefits offered by this job

Remote work

Competitive salary

Home office setup

Flexible hours

Paid leave

Mentorship & growth

Job summary

BairesDev is hiring an AI Engineer to build and deploy AI-powered applications through model APIs and orchestration frameworks. You will focus on integrating AI into existing workflows to deliver measurable value and robust engineering patterns.

You will design AI features, develop RAG pipelines, manage vector databases, and optimize latency and token usage while collaborating with product teams to deliver scalable AI solutions.

Qualifications

• 4+ years of experience in Software Engineering or AI Engineering.
• Proven expertise in building applications using LLM APIs and orchestration frameworks.
• Hands-on experience with RAG (Retrieval-Augmented Generation) and vector databases.
• Proficiency in embeddings and semantic search.
• Deep understanding of practical AI integration within the application layer.

Responsibilities

• Design and implement AI-driven features using LLM APIs and prompt engineering techniques.
• Develop and manage Retrieval-Augmented Generation (RAG) pipelines to ground model outputs in specific data.
• Architect and maintain vector databases to support efficient semantic search and information retrieval.
• Integrate embeddings and vector search into production applications to enhance user experience and personalization.
• Optimize AI application performance by managing latency, token usage, and retrieval accuracy.
• Collaborate with product teams to translate business requirements into scalable, production-grade AI solutions.

Skills

LLM APIs

RAG

Vector databases

Embeddings

Semantic search

Tools

LLM orchestration frameworks

Vector databases

Job description

BairesDev is hiring an AI Engineer to build and deploy AI-powered applications through model APIs and orchestration frameworks. You will focus on integrating AI into existing workflows to deliver measurable value and robust engineering patterns.

You will design AI features, develop RAG pipelines, manage vector databases, and optimize latency and token usage while collaborating with product teams to deliver scalable AI solutions.