Multi-Regional Context Engineer (RAG / Knowledge Base)

Mission: Design and operate a multi-region Knowledge Base (KB) architecture with regional overlays, strong retrieval
accuracy, SME validation workflows, and shared support for both NB and MODS.

Key Responsibilities:
Build and implement KB architecture with base layer and regional overlays
Seed KB across 12 regions
Develop ingestion pipelines from structured docs to embeddings and retrieval-ready content
Implement approval and promotion workflow (draft approved live)
Maintain retrieval quality metrics and KB integrity
Add MOD-specific overlays

Must-Have Skills:
4 6 years of experience in RAG and vector search systems
Experience building multi-tenant and multi-region retrieval architectures
Familiarity with Vertex AI Vector Search, Pinecone, Weaviate, and OpenSearch
Strong understanding of retrieval metrics such as recall@k, precision@k, and MRR
Python and document ingestion pipeline experience

Nice-to-Have Skills:
KB lifecycle management and audit workflows
Human-in-the-loop workflows
Telecom / RF familiarity