Software Engineering · CSULB '28 · Los Angeles
Computer Science student at CSULB building full-stack web products — booking platforms, AI tools, and modern web experiences.
Seeking Software Engineering internships for Summer 2026 and 2027. Currently building a booking platform for an LA-area hotel.
I'm a CS student at CSULB ('28), minoring in Finance. My work sits between full-stack engineering and product thinking — I care about clean code, but I care just as much about whether what I build is actually useful to the person on the other side of the screen.
Right now I'm building the first website and booking platform for an LA-area hotel, shipping production code in Next.js and TypeScript with Stripe for payments. Alongside that, I work on Python and Flask projects for AI tooling, backend services, and small utilities. Recognized on the CSULB President's Honor List.
Next.js, TypeScript, Tailwind, React on the frontend. Python, Flask, Stripe, AWS on the backend. Equally comfortable on either side.
Use Claude Code, Codex, and Copilot to plan, ship, and review work — never to skip code review or testing.
DSA practice via NeetCode. AWS Certified Cloud Practitioner. CSULB President's Honor List.
A working portfolio of recent work — a booking platform, AI tools, a video generator, and the site you're reading this on.
First-party website and booking platform for an operating LA-area hotel. Replacing a third-party booking dependency with a Stripe-powered reservation flow, plus a separate ordering subsystem for on-property services.
In development, v1 launching May 2026.
Premium animated personal portfolio in Next.js 16, TypeScript, and Tailwind v4 with motion animations, full WCAG AA accessibility, and a custom warm-light design system. Built with Claude Code and Codex in an AI-paired workflow.
The site you're reading this on.
Flask REST service that takes uploaded media, generates TTS narration, and renders short videos via an ffmpeg pipeline. Includes job-status polling, rate limiting, exponential-backoff retries, and structured logging.
Released October 2025.
Depth varies by area — frontend and Python/Flask are strongest, AWS and Stripe are growing through current projects.
I use AI tools the way I use any tool — to plan more clearly, ship faster, and catch mistakes earlier. Every line of generated code is reviewed before it gets committed. Here's how I actually work.
Step 1
Use Claude and ChatGPT to think through requirements, edge cases, and architecture before writing code. Document decisions in markdown.
Step 2
Pair with Claude Code or Codex inside VS Code for implementation. Write typed, reviewable code in small commits.
Step 3
Run lint, build, type checks, and manual review at every phase boundary. Fix what's broken before moving forward.
Step 4
Deploy via Vercel from GitHub. Smoke test the live build. Monitor and iterate based on real use.
Best reached by email. Currently in Los Angeles and open to remote, hybrid, or on-site roles for Summer 2026 and Summer 2027 cycles.