Description

You will design and implement production-grade LLM and RAG systems.

This role is hybrid.

Responsibilities

• Implement Retrieval-Augmented Generation (RAG) in production, managing chunking, ranking, and retrieval nuances.
• Design multi-step LLM prompt chains and evaluate outputs using manual methods or LLM-as-a-judge.
• Select and deploy appropriate models such as Sonnet or GPT series.
• Develop Python scripts for data processing, analysis, and automation.
• Support data engineering tasks including managing SQL databases and Solr/OpenSearch.

Required Skills

• 5+ years of experience in Data Science or related fields.
• Deep expertise in Large Language Models (LLMs) and RAG architectures.
• Advanced prompt engineering skills for complex, multi-step chains.
• Proficiency in Python for data processing and scripting.
• Experience with SQL databases.
• Knowledge of Solr or OpenSearch.
• Understanding of CI/CD pipelines and data engineering principles.
• Experience with NLP.

Preferred Skills

• Experience with LangChain, LLaMA models, and Agentic RAG.
• Hands-on experience with AWS.

Key Skills

Education

Any Gradute