RAG Engineers + AI Developers
Core
Design and optimize production-grade Retrieval-Augmented Generation (RAG) systems for enterprise knowledge environments, handling document ingestion, retrieval, and application integration.
Role type
Senior IC RAG Engineer (AI/ML)
Builds
Scalable RAG pipelines, vector/hybrid search solutions, and customer-facing AI applications
Domain
Enterprise AI, Information Retrieval, NLP
Deliverable
production ML models
Required skills
RAG architecture, vector databases, Python, LLMs, semantic search, document processing, retrieval optimization
Preferred skills
Hybrid search, reranking, automated evaluation frameworks
Technologies
Pinecone, Qdrant, Weaviate, OpenSearch, LangChain, LlamaIndex
Responsibilities
Design end-to-end RAG pipelines; Build vector and hybrid search solutions; Implement advanced retrieval strategies; Develop document processing workflows; Integrate RAG components into applications; Establish automated evaluation frameworks; Optimize system latency and scalability
Seniority
Senior, hands-on IC
