I’m a Software Engineer and CS Major at the University of Oklahoma, returning to Google full-time in 2027. Most recently, I completed a Software Engineering Internship at Google Cloud (Summer 2026) on the Data Protection team, where I worked on enterprise data security UI modernization and telemetry pipelines for the Google Admin Console.
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: Product-facing Work, Cloud Infrastructure, Applied AI and Distributed backend systems.
- 🎓 Education: Accelerated B.S. / M.S. in Computer Science at the University of Oklahoma.
- 🏗️ I care about: Performant and Scalable Systems designs, Bridging low-latency backend systems with intuitive consumer interfaces, optimistic UI architecture, and shipping at high velocity.
- 🧰 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 |
|---|---|---|---|
| Software Engineering Intern | TypeScript, Material Design 3, gRPC, Protocol Buffers, Jasmine, Java | Modernized a rule-creation engine for the Data Protection team in Google Admin Console, refactoring legacy JS to TypeScript + Material Design 3 to reduce tech debt by 30%. Profiled client-to-server pipelines to cut frontend rendering times by 15%. Integrated LLM-driven evaluation over gRPC/Protobuf streaming with feature flags. | |
| 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 architecture, sustaining 99.9% uptime during live spikes. Split workload into Batch Training (S3/EC2) and Real-Time Inference (Lambda/DynamoDB), cutting latency 50%. |
| K20 Educational Research Center | Software Engineer Intern | TypeScript, React, AdonisJS, PostgreSQL, Docker, Kubernetes (GKE), WebSockets | Developed an enterprise platform using React + AdonisJS + Postgres, tuning connection pooling to reduce p95 latency by 40%. Deployed containerized microservices on GKE with WebSocket token-streaming, cutting end-to-end response times by 60%. |
| Sooner Competitive Robotics | Software Engineer Intern | Python, C++, Linux, TensorFlow, PyTorch | Built real-time concurrent robot navigation and control modules in Python/C++, contributing to a 1st-place finish. Implemented telemetry-based sensor tuning, raising navigation precision by 30%. |
| Project | Role | Stack | Key Achievements |
|---|---|---|---|
| Echoes | Lead iOS & ML Developer | Swift, SwiftUI, Vision, SFSpeechRecognizer, SwiftData, CoreML, CoreHaptics | Developed an on-device accessibility and journaling iOS app for the Apple Swift Student Challenge. Integrated Vision facial tracking and real-time SFSpeech audio transcription with on-device CoreML sentiment analysis for private, zero-latency affective feedback. |
| Pitchly | Full-Stack Engineer | Next.js, TypeScript, Python, FastAPI, WebSockets, OpenAI API, TailwindCSS | Built an AI-driven mock interview platform that conducts conversational behavioral/technical screeners. Implemented token-streamed audio/text analysis over WebSockets with instant scoring heuristics and feedback telemetry. |
| QuickNews.ai | Full-Stack Developer | JavaScript, Next.js, AWS Lambda, API Gateway, CloudWatch, AWS Comprehend | Shipped a Next.js platform powered by AWS serverless APIs for dynamic news extraction and sentiment analysis. Configured Provisioned Concurrency to slash median execution latency from ~2.0s down to ~200ms (10x reduction). |
If you're building performance-critical systems, developer tools, or AI infrastructure, I’m always down to talk.
