I’m an Incoming Software Engineering Intern at Google (Summer 2026), joining the Data Protection team to help build the next generation of the rule creation engine in Google Admin Console with AI-driven workflows. Right now (Spring 2026), I’m interning at Metron Analytics, redesigning a live sports prediction platform into a serverless AWS architecture. I love building systems and products that are used to solve real world problems at scale. I'm particularly interested in real-time data, serverless pipelines, and production constraints.
- 🧠 Core interests: Software Engineering in Cloud Infrastructure, Backend systems, Developer Platform and, AI tooling.
- 🎓 Education: BSc in Computer Science at the University of Oklahoma.
- 🏗️ I care about: Performant and efficient System designs, end-to-end latency, clean API pipelines, and shipping
- 🧰 Personal hobbies: F1 Racing (everything racing), Go Karting, Video Games, and building cool stuff.
- Simple interfaces → strong invariants → measurable performance
- Build the minimum that ships, then iterate with instrumentation
- Prefer boring tech for the core, and sharp tools at the edges (AI, streaming, UX polish)
| Category | Stack |
|---|---|
| Languages |       |
| Frameworks & UI |      |
| Cloud Infra & DevOps |       |
| AI/ML |      |
| Database |      |
| Tools & Design |       |
| Company | Role | Stack | Key Achievements |
|---|---|---|---|
| Metron Analytics LLC | Software Engineering Intern | Python, FastAPI, AWS (Lambda, EventBridge, DynamoDB, S3, EC2), PostgreSQL (Supabase), Neon | Migrated the live sports prediction backend from FastAPI/Railway to an event-driven AWS serverless stack, sustaining 99.9% uptime during game spikes. Split the pipeline into Batch Training (S3/EC2) + Real-Time Inference (Lambda/DynamoDB), cutting inference latency 50%. |
| K20 Educational Research Center | Software Engineer Intern | TypeScript, React, AdonisJS, PostgreSQL, Docker, Kubernetes (GKE), WebSockets, GitHub Actions, Google Cloud Observability | Built and shipped a platform with React + AdonisJS + Postgres, optimizing pooling to reduce p95 latency 40%. Deployed Docker services on GKE with WebSocket token-streaming, reducing end-to-end response time 60%. |
| Sooner Competitive Robotics | Software Engineer Intern | Python, C++, Linux, TensorFlow, PyTorch | Built real-time robot control modules in Python/C++ using concurrent patterns, contributing to a 1st-place finish. Added telemetry-driven tuning that improved navigation precision by 30%. |
| Project | Role | Stack | Key Achievements |
|---|---|---|---|
| QuickNews.ai | Full-Stack Developer | JavaScript, Next.js, AWS Lambda, API Gateway, CloudWatch, AWS Comprehend | Shipped a Next.js app with serverless APIs for news summaries and sentiment analysis. Used Provisioned Concurrency to cut median latency ~2.0s → ~200ms (10x). |
| Autocomplete Search Engine | Full-Stack Developer | Java, Spring Boot, TypeScript, Angular, PostgreSQL, Redis | Built a search experience with prefix lookup + filtering for role-based usage, handling 100+ concurrent queries. Added Redis caching + query profiling to cut lookup latency by 15%. |
If you're building performance-critical systems, developer tools, or AI infrastructure, I’m always down to talk.
