Production RAG: indexing, retrieval, hybrid search, reranking, citations
Context Graph: entity resolution, linking, provenance; graph + vector retrieval
LLM orchestration: tool/function calling, structured outputs, routing across model tiers
GPU/inference cost optimization: batching, caching, quantization, autoscaling
Safety + compliance: PII/PHI handling, redaction, audit logs, deterministic replay
LLMOps: eval harness (golden sets, regression, adversarial)

🎯 Requirements

5+ years building production systems; 2+ years hands-on LLMs/RAG
Proven RAG experience (embeddings, vector DBs, hybrid search, reranking, eval)
Strong backend/distributed systems + observability
Track record shipping in high-stakes environments with auditability/correctness
Knowledge graph / entity resolution / provenance systems
GPU inference optimization (vLLM/TGI/TensorRT-LLM, quantization AWQ/GPTQ, batching)

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