Experience
Current Role
Founder & CEO, PicQR AI
Building PicQR AI from MVP into a company that combines images with QR to create fully scannable, image‑styled QR codes. More to come.
Previous Experience
Software Engineer - AI & Graph at BlueArc
September 2024 - August 2025
- Owned and scaled the core distributed system, reducing error rates by >98% and increasing throughput by >100×.
- Implemented row-level security in PostgreSQL and a Redis enforcement layer to guarantee strict per-customer access controls.
- Wrote/refactored approximately 30–40% of BlueArc process steps across the platform, with major increases in automated test coverage.
- Built a status-code–based custom retry framework mirroring HTTP semantics to harden external integrations and background jobs.
- Developed most customer-specific process steps for a multi-billion-dollar pilot, converting it from pilot to paying customer.
- Designed a global database connection pooler, authored deployment scripts, and provisioned new PROD/DEV environments.
- Created a custom abstraction language plus supporting internal tools to accelerate delivery and reduce defects.
- Interviewed, hired, and trained engineers; contributed to architecture decisions around graph theory, caching, and service design.
Software Engineering Intern at BlueArc
May 2024 - September 2024
- Developed core frameworks for BlueArc’s LLM-powered automatic risk-management and compliance system
- Key contributions in API integration, prompt engineering, and embedding systems
Computer Science & Math Trainer at DataAnnotation
May 2024 - Present
- Specializes in prompt engineering and evaluating LLM responses
- Guides LLMs to solve complex Math & CS problems
Computer Science Trainer at Scale AI (Outliers)
February 2024 - Present
- Reviews and assesses AI-generated code for accuracy and quality
CPU Machine Learning Co-Op/Intern at AMD
May 2023 - Aug 2023
- Created a project focused on partial quantization of convolutional neural networks (CNNs)
- Developed and applied genetic algorithm to quantize 90% of CNN nodes
- Achieved dramatic model size reduction with only 0.2% accuracy loss (vs 10% with full quantization)
- Reduced memory usage and sped up inference times for resource-constrained devices
Captain, Barn2Robotics FRC Team 751
2021 - 2022
- Led team organization, scheduling, and budget management
- Taught CAD and the design process
- Spearheaded recruitment efforts and managed component leads