Azure AI Engineer (RAG Optimization)

• Optimize an existing Azure AI Foundry RAG implementation.
• Improve retrieval accuracy, ranking, reranking, and context selection.
• Configure and refine document ingestion, chunking, metadata tagging, indexing strategies, and search optimization.
• Evaluate and tune development and staging environments to improve response quality.
• Analyze large document sets including manuals, specifications, and technical documentation to improve retrieval effectiveness.
• Enhance prompt engineering and context window strategies to improve first-response accuracy.
• Work with business and technical teams to implement a backlog of planned enhancements.
• Test and validate retrieval and response quality using real-world customer support use cases.

Required Experience

• Hands-on experience with Azure AI Foundry.
• Experience building, tuning, or optimizing Retrieval Augmented Generation (RAG) solutions.
• Strong understanding of document ingestion, chunking strategies, metadata tagging, indexing, ranking, and reranking.
• Experience improving search relevance and retrieval accuracy within AI applications.
• Knowledge of vector search, semantic search, and retrieval optimization concepts.
• Experience testing and validating prompt strategies and AI response quality.
• Ability to work independently and deliver enhancements within an established environment.