AI Engineer (RAG) - Remote Work

BairesDev; Comisión de Fomento de Perú; Remote; ARS 185,819,000 - 278,728,000; Full time

Benefits offered by this job

100% remote work (from anywhere)

Excellent compensation in USD or your

Hardware and software setup for you to

Flexible hours: create your own

Paid parental leaves, vacations, and

Innovative and multicultural work env.

Mentorship and growth opportunities

Job summary

BairesDev is seeking an experienced AI Engineer specializing in Retrieval-Augmented Generation (RAG) to design and implement end-to-end RAG pipelines and integrate with external knowledge bases. You will work remotely on enterprise-grade projects, delivering grounded, high-quality responses while minimizing hallucinations.

You will collaborate with data and software teams, optimize vector databases, experiment with chunking and reranking, and evaluate performance using established frameworks.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Python

RAG

Embeddings

Reranking

English

Tools

Pinecone

Qdrant

Weaviate

Job description

At BairesDev®, we've been leading the way in technology projects for over 15 years. We deliver cutting-edge solutions to giants like Google and the most innovative startups in Silicon Valley.

Our diverse 4,000+ team, composed of the world's Top 1% of tech talent, works remotely on roles that drive significant impact worldwide.

When you apply for this position, you're taking the first step in a process that goes beyond the ordinary. We aim to align your passions and skills with our vacancies, setting you on a path to exceptional career development and success.

AI Engineer (RAG) at BairesDev

As an AI Engineer specialized in RAG, you will design and implement advanced retrieval-augmented generation systems to enhance the accuracy and reliability of large language models. You will connect generative AI with external knowledge bases, ensuring that responses are grounded in factual, domain-specific data while minimizing hallucinations.

What You'll Do:

• 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.

What we are looking for:

• 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.

How we do make your work (and your life) easier:

• 100% remote work (from anywhere).
• Excellent compensation in USD or your local currency if preferred
• Hardware and software setup for you to work from home.
• Flexible hours: create your own schedule.
• Paid parental leaves, vacations, and holidays.
• Innovative and multicultural work environment: collaborate and learn from the global Top 1% of talent.
• Supportive environment with mentorship, promotions, skill development, and diverse growth opportunities.