Creative Technologist & AI Agent Developer

I design and build production-grade AI agent systems — from single-agent RAG pipelines to multi-agent orchestration frameworks. My work spans agentic workflow design, retrieval-augmented generation, prompt engineering, full-stack AI applications, enterprise AI architecture, real-time streaming systems, and serverless deployment patterns. I also apply generative AI tools and prompt engineering techniques to produce commercial brand imagery for major retail clients.

Based in US & EU/Ireland.

🌐 paulforlando.com | 💼 LinkedIn | 📧 Available for freelance & consulting

Single Agents → Multi-Agent Systems → Enterprise Orchestration Pipelines → Real-Time Full-Stack AI Applications → Serverless Production Systems

I focus on agents that are production-ready — properly configured, defensively prompted, designed to fail gracefully, and protected with cost controls and rate limiting. Not just demos.

Multi-agent trading system with real-time streaming and production safety controls

A visually stunning AI-powered trading platform demonstrating multi-agent orchestration, real-time data streaming, domain-specific logic, and enterprise-grade cost protection:

• 5-Agent Orchestration: Portfolio (execution), Risk (validation), Analyzer (insights), Watchlist (management), Chat Orchestrator (LLM routing)
• Real-Time Streaming: Server-sent events (SSE) for live price updates with flash animations
• Domain Logic: Portfolio mathematics, P&L tracking, position constraints, audit logging
• Testing: Playwright E2E suite (10 tests, 4 consecutive fresh runs, all passing)
• Cost Protection: Dual-layer rate limiting (15 chat/hr, 20 trades/hr code-level + $5 monthly provider cap)
• Deployment: Docker multi-stage build, Railway serverless, automatic health checks

Pattern: Deterministic agents (Risk, Portfolio, Analyzer) + LLM orchestrator → Real-time state management → Atomic transactions → E2E tested

GitHub: multi_agent_trading_app
Live: multiagenttradingapp-production.up.railway.app

Stack: FastAPI · Next.js · SQLite · Playwright · Cerebras/OpenRouter · SSE · Railway

Production-ready enterprise agentic AI on AWS

A fully functional travel booking agent demonstrating serverless multi-tool agent orchestration:

• Agent Framework: Strands SDK + Bedrock Nova Lite
• Memory: S3 SessionManager for persistent conversation history
• RAG: Bedrock Knowledge Bases for private data access
• Extensibility: Model Context Protocol (MCP) dynamic tool loading
• API: Secure HTTP via API Gateway + Cognito OAuth2
• Scale: Handles 1000+ concurrent requests, ~$0.02/request

Pattern: Multi-tool orchestration → Persistent memory → RAG integration → Secure API exposure

GitHub: serverless-agentic-ai-travel-agent

Stack: Strands SDK · Bedrock · Lambda · API Gateway · Cognito · S3 · Knowledge Bases

I use generative AI tools with prompt engineering techniques to produce brand imagery for major retail clients across the following disciplines:

• Generative AI Image Creation
• AI Art Direction
• Commercial Product Visualization
• Lifestyle Imagery

🔗 View Portfolio on ArtStation | Repository

Agent Design — tool routing, prompt engineering, multi-agent orchestration, supervisor patterns, retrieval-augmented generation, hallucination detection, moderation, memory, full-stack AI applications, MCP server development, serverless agent deployment, real-time streaming systems

Cloud & Infrastructure — AWS Lambda, API Gateway, Bedrock, Cognito, S3, Knowledge Bases, CloudWatch, serverless architecture patterns, Railway, Docker multi-stage builds

Stack — Flowise · LangChain · OpenAI API · Python · FastAPI · Next.js · n8n · TypeScript · OpenRouter · Exa · Postgres · FAISS · Neon · Supabase · Claude Code · Pinecone · FastMCP · MCP Protocol · Railway · Vercel · Strands SDK · Cerebras

Disciplines — 3D Visualization · Generative AI · Data Analytics · AI Product Visualization · Serverless Architecture · Real-Time Systems

Every agent in this portfolio is built with the same standard:

• Explicit, rule-based system prompts — no vague instructions
• Tool descriptions written as policies, not labels
• Temperature tuned to the use case — not left at default
• Failure modes addressed — iteration caps, moderation, fallbacks
• Production considerations documented — memory, security, deployment, cost controls

Every live application in this portfolio is built with production-grade security and cost controls — not just functional demos.

Real-Time System Resilience FinAlly demonstrates real-time state management with SSE streaming, connection status indicators, automatic reconnection, and atomic database transactions. The system handles concurrent requests with in-memory rate limiting and maintains audit logs for compliance.

MCP Server Security Custom MCP servers implement API key authentication (X-API-Key header, 401 on invalid key) and sliding-window rate limiting (5–10 requests/IP/hour, 429 on exceed) with self-host instructions embedded in every error response. Rate limiting is implemented as pure middleware without third-party auth frameworks — correct IP detection behind Railway's proxy via X-Forwarded-For header parsing.

AWS Lambda Security & Scalability The serverless agentic AI system implements Cognito OAuth2 authentication, per-user session isolation, S3-backed state management, and automatic horizontal scaling. Infrastructure costs are controlled through serverless pay-per-use pricing (~$0.02/request), with no idle server overhead.

Cost Protection All LLM API keys (OpenAI, OpenRouter) are capped at hard monthly spend limits. Exa AI auto-recharge is capped per calendar month. Rate limiting at the infrastructure layer provides the first line of defense; spend caps at the provider level provide a hard ceiling if rate limiting is ever bypassed.

Production AI systems require controls at every layer — request-level rate limiting, infrastructure-level authentication, provider-level spend caps, and cloud-native security. Each application in this portfolio is built with these standards, reflecting practices applied in enterprise deployments where cost, security, reliability, and real-time performance are non-negotiable.

Open to collaboration on agent design, AI workflow architecture, serverless AI systems, real-time applications, and creative technology projects.