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Niche LLM/Azure RAG specialization and senior-level requirement limit applicant density.
Specialized LLM, Azure AI Search, and enterprise retrieval requirements limit cross-industry transfer.
Multiple mandatory specialized technologies and enterprise RAG experience increase shortlisting strictness.
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Build and maintain secure AI search and retrieval systems for large-scale enterprise document platforms utilizing Azure AI Search and Azure OpenAI.
Design and implement retrieval-augmented generation (RAG) solutions, vector search, semantic ranking, and relevance tuning grounded in enterprise data.
Develop backend services integrating search, retrieval, and LLM calls ensuring scalability, resiliency, observability, and compliance with security and governance standards.
Proficiency in Python and backend engineering experience (Java or Python).
Hands-on experience with Large Language Models (LLMs), prompt engineering, Azure OpenAI SDKs and APIs.
Experience in enterprise document platform search and retrieval (Azure AI Search / Cognitive Search) including vector and hybrid search approaches.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in designing and leading enterprise-scale retrieval-augmented generation (RAG) platforms with strong AI architecture influence.
Familiar with security-aware retrieval including document-level access control and metadata-driven filtering for compliance.
Skilled in balancing accuracy, explainability, compliance, and cost in AI search solutions, and mentoring engineers in AI search/retrieval patterns.