Information Retrieval Engineer

Job description

Job Details We are seeking a highly skilled Information Retrieval Engineer to lead the development and optimization of retrieval systems that power context-aware large language models (LLMs). This role focuses on building robust Retrieval-Augmented Generation (RAG) pipelines to ensure AI agents and applications have access to the most relevant, timely, and high-quality information. You'll work at the intersection of data engineering, machine learning, and knowledge management—enabling better reasoning, accuracy, and performance for enterprise-grade AI systems. Key Responsibilities: RAG System Design: - Architect and deploy scalable retrieval pipelines using vector databases (e.g., FAISS, Weaviate, Pinecone, Qdrant) - Implement semantic search infrastructure and hybrid retrieval systems (semantic + keyword) Data Processing & Ingestion: - Build ingestion pipelines for both structured and unstructured data sources - Implement document chunking strategies, embedding generation (e.g., OpenAI, Cohere, HuggingFace), and metadata tagging Retrieval Optimization: - Fine-tune relevance scoring, reranking algorithms, and query understanding mechanisms - Develop techniques to improve precision/...