Paul Raymond Tive

LLM Systems Architecture • Multi-Agent Orchestration • AI Observability

Architecting intelligent AI infrastructure that moves beyond prototypes — building governed, observable, production-ready LLM systems and multi-agent orchestration platforms engineered for real-world scale, reliability, and long-term evolution.

Download Resume (PDF)

Technical Impact

Production-grade AI engineering with controlled orchestration, security safeguards, and measurable system behavior.

Live AI Orchestration

Production-grade LLM orchestration layer integrating GPT with structured prompts, role-based governance, deterministic routing, and execution trace visibility.

Abuse-Resistant Design

Enterprise-aware safeguards including email gating, IP rate limiting, token caps, and request validation to prevent misuse and enforce operational cost control.

Observability & Metrics

Real-time latency measurement, response confidence scoring, and retrieval trace transparency surfaced directly in the interface for measurable AI system behavior.

Modular Architecture

Separated frontend (Next.js), API gateway (FastAPI), orchestration layer, and model interface with clearly defined boundaries for scalability and cloud deployment.

System Architecture Overview

Engineering Impact Metrics

AI Systems Engineered

RAG Architectures Designed

Cloud Deployments

Custom Built Infrastructure

Production AI Systems

Multi-Agent AI Orchestration

Designed and built modular multi-agent architecture with governance layers, semantic merging, and structured task execution pipelines.

RAG + Vector Retrieval Infrastructure

Implemented Retrieval-Augmented Generation pipelines with structured databases, vector embeddings, and cost-aware orchestration.

Production AI Deployment

Deployed AI systems using serverless infrastructure, API gateways, authentication layers, and observability tools.

Technical Stack

PythonFastAPIOpenAI APIAWSServerlessVector DatabasesPostgreSQLNext.jsDockerLLM InfrastructureMulti-Agent SystemsRAG Pipelines

Production Impact Highlights

Scalable AI Architecture

Designed modular RAG and multi-agent systems structured for extensibility, separation of concerns, and cloud deployment readiness.

Governed AI Execution

Implemented structured retrieval, validation layers, cost-awareness, and system-level guardrails to ensure reliable AI response generation.

Production Deployment

Deployed AI systems with backend APIs, vector databases, authentication-ready structure, and scalable hosting environments.