🛠 Tech Stack

💼 About This Role

You'll build AI search agents and end-to-end RAG pipelines for production, using frameworks like LangGraph or CrewAI. Your work will directly impact the quality of AI-generated answers through grounding and citation.

🎯 What You'll Do

• Design and build AI search agents using ReAct or multi-agent architectures
• Develop end-to-end RAG pipelines with hybrid vector search in OpenSearch
• Implement grounding and citation for generated answers
• Automate evaluation with synthetic QA and retrieval-hit-rate tracking

📋 Requirements

• 3+ years of experience developing AI systems with a focus on RAG
• Proven track record in building end-to-end RAG pipelines
• Hands-on experience with OpenSearch or similar vector search technologies
• Proficiency in Python and machine learning frameworks like PyTorch or TensorFlow

✨ Nice to Have

• Experience with AI search agent frameworks like LangGraph, Dify, or CrewAI
• Familiarity with synthetic QA datasets and evaluation metrics
• Knowledge of data ingestion, chunking, and embeddings techniques