Bridging legacy enterprise infrastructure with modern foundation models, vector retrieval pipelines, and verifiable zero-trust governance.
Connecting LLMs and vector databases with SQL databases, mainframe queues, ERPs, and internal REST APIs without compromising data integrity or existing business logic.
Implementing hardware-attested, on-premise proxy filters that sanitize PII, block prompt injection attacks, and enforce strict role-based access control before payloads hit LLM providers.
Architecting scalable RAG systems combining sparse BM25 keyword search with dense vector embeddings (pgvector, Qdrant, Pinecone) and cross-encoder re-ranking pipelines.
Drastically reducing inference cost and API latency by routing similar prompts through Redis vector caching, local Ollama/vLLM fallbacks, and intelligent prompt compressions.
Exposing AI capabilities as secure REST/gRPC microservices with rate limiting, load balancing, model failover routing, and complete Prometheus telemetry.
Gene Da Rocha brings senior architectural leadership across cloud-native microservices, enterprise security compliance, and state-of-the-art LLM pipeline design.