AI Engineer - RAG & Semantic Search

Build and optimize APIs and backend integrations; Build vector databases for retrieval; Contribute to software architecture and infrastructure; Create embedding pipelines for document ingestion and chunking; Design SQL and NoSQL data models and schemas; Design and develop scalable applications; Develop semantic search and retrieval mechanisms; Diagnose and resolve technical issues; Evaluate RAG pipeline quality; Implement NL to SQL interfaces using LLMs; Perform code reviews and provide feedback