Full Profile
MS

Matt Spaulding

I build production AI systems that work under real constraints. With 15+ years designing and scaling software across startups and enterprise environments, I operate at the intersection of architecture and product. I take ambiguous AI ideas and turn them into structured, reliable systems that ship.

Location

Tampa, FL

Work

Remote · On-site

Employment

Full-time · Part-time

Education

University of South Florida
2008 — 2011
Master of Science - MS in Computer Engineering
Founder Institute
2025-05 — 2026-02
Startup Accelerator Program

Skills

Technology DesignProgrammingSystems Analysis

Knowledge Areas

Computers and ElectronicsEngineering and TechnologyMathematics

Work Styles

Analytical ThinkingAchievement/EffortPersistence

Technology

AI System ArchitectureOpenAI CodexPrompt Engineering

Languages

English · Native or Bilingual

Community & Publications

Build Ultra-Modern Web Apps with Angular Material
ASP.NET MVC 4 WEB API with Code First Migrations Hands On

Experience

Founder & AI Product Lead
Beesla
2025-04 — Present
  • Founded and built an AI-native job discovery platform that converts natural language career searches into structured job results using agent-driven workflows.
  • Designed and implemented the production LLM architecture powering the platform, including prompt orchestration, structured outputs, tool calling, retrieval integration, and reliability guardrails.
Chief Technology Officer
JobPhaze
2024-04 — 2025-04
  • Led technical architecture and engineering execution for an early-stage SaaS platform, defining infrastructure, data models, and scalable deployment patterns from initial development through production release.
  • Designed the system architecture supporting application services, data pipelines, and cloud infrastructure to ensure reliability and long-term scalability.
Chief Technology Officer
Weaver
2023-04 — 2024-04
  • Directed engineering and system architecture for an early-stage SaaS platform, leading development from initial system design through production deployment.
  • Defined scalable architecture patterns and infrastructure strategy to support rapid product iteration while maintaining long-term maintainability.
  • Established engineering workflows, deployment practices, and operational standards to ensure reliable production releases.