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Quant systems / AI infrastructure / low-level engineering

Saul Dugan

I build quantitative trading systems, AI-assisted research tools, and low-level software.

Focused on futures trading infrastructure, backtesting, risk controls, Palantir Foundry workflows, and systems-level engineering.

Featured projects

Technical work across trading systems, research tooling, and low-level software.

Each card links to a case-study page with placeholders for screenshots, results, and source links.

Screenshot TODO

AEM / Strategy Research OS

A research operating system concept for organizing strategy ideas, experiment history, validation notes, and decision records.

  • Research workflow
  • AI-assisted analysis
  • Strategy validation
Read case study
Screenshot TODO

Macro Event Risk Filter

A risk-control concept for filtering trading activity around scheduled macro events and other high-volatility windows.

  • Macro events
  • Risk filter
  • Trading operations
Read case study

Skills

A practical stack for building and validating technical systems.

Quant & Trading Systems

  • Futures
  • Backtesting
  • Risk controls
  • Pine Script
  • NinjaTrader
  • Strategy validation

Data & AI

  • Python
  • pandas
  • NumPy
  • Market data pipelines
  • AI-assisted research
  • Overfit analysis

Foundry / Product Systems

  • Palantir Foundry
  • Ontology modeling
  • Workshop apps
  • Operational workflows

Systems Programming

  • C
  • C++
  • C#
  • APIs
  • Webhooks
  • Memory management
  • Automation agents

Frontend / Web

  • Astro
  • TypeScript
  • Tailwind
  • GitHub
  • Cloudflare Pages

About

Builder at the intersection of markets, systems, and automation.

I’m a technical builder interested in the intersection of financial markets, software systems, AI-assisted research, and practical automation. My work focuses on turning messy real-world workflows into structured systems: ingesting data, defining models, validating decisions, and building tools that can actually be used.

Contact

Links and resume

Replace the TODO placeholders when your public profiles are ready.

Email
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GitHub
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LinkedIn
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Resume PDF
/resume.pdf