Software Engineer | Founding Engineer | Systems & Infrastructure
I am a software engineer and founding engineer focused on building and scaling production systems across cloud infrastructure, backend services, and full-stack applications. I specialize in taking products from zero to production, designing reliable systems, and owning architecture end-to-end.
While my professional work centers on infrastructure and backend engineering, I actively build AI/ML systems in my free time, with a focus on LLMs, data pipelines, and applied machine learning.
- Building and scaling production systems at F4 Industries
- Designing secure cloud infrastructure and CI/CD pipelines on GCP
- Developing backend services in Rust and Python for real-world applications
- Exploring AI/ML systems and LLM applications in personal projects
- Built and scaled production systems, transitioning prototypes into Rust-based services
- Architected full GCP backend infrastructure (auth, licensing, secure services)
- Owned CI/CD pipelines and deployment for multiple live customer-facing products
- Developed core systems including OCR/PDF pipelines, file processing, and backend services
- Delivered features for enterprise React + Nx applications hosted on AWS
- Built licensing and subscription systems with Stripe for multi-tenant platforms
- Developed admin tooling and improved UI/UX across client-facing systems
- Led development of software, ML systems, and APIs across 20+ research projects
- Built data pipelines, OCR systems, and large-scale analysis tools
- Developed and deployed LLM-powered applications and evaluated local models
- Created HPC workflows using multiprocessing and parallel computing
-
Penny (AI Financial Advisor)
AI system that analyzes transaction data and generates personalized financial insights -
LLM API (Local + Cloud Hybrid)
REST API for running LLMs (Llama, Mixtral) locally for privacy-focused workflows -
PubMed Dashboard
Data platform processing thousands of research papers with real-time visualization -
Library AI Chatbot (RAG)
Full-stack chatbot using embeddings and retrieval-augmented generation
- Distributed systems design and fault-tolerant architectures
- Low-level performance optimization in Rust
- Advanced LLM systems, evaluation, and retrieval techniques
- Scalable data infrastructure and streaming systems
- Backend-heavy or infrastructure-focused projects
- Distributed systems and scalable platforms
- AI/ML projects (LLMs, data pipelines) on the side
- Distributed Systems and Cloud Infrastructure (GCP, AWS, CI/CD)
- Backend Engineering (Rust, Python, APIs, Microservices)
- System Design and Production Architecture
- High-Performance Computing and Parallel Processing
- AI/ML Systems (personal projects)
Languages: Rust, Python, TypeScript, JavaScript, C/C++
Backend: FastAPI, Flask, REST APIs, Microservices
Cloud: GCP, AWS, Terraform, CI/CD
Frontend: React, HTML/CSS
Data/ML: PyTorch, TensorFlow, OpenCV, LLMs
Tools: Docker, GitHub Actions, OAuth/JWT, Stripe