Open to New Grad SWE roles · Starting January 2027
I build reliable, scalable systems end-to-end, from AI pipelines to serverless backends. Founder of Kintec AI, Backend Software Engineer at IBM, and Computer Science student at Purdue University.
Contact MeI didn’t know much about computers when I took my first AP Computer Science class. I fell in love with the idea of coding and was really interested in pursuing it in college, so I did.
At Purdue I dove into CS fundamentals, but after my sophomore year I felt the need to build something real and valuable that people would actually love. That’s when I cofounded Kintec AI with Tyson Magee (DNP, FNP-BC) and Kayden Froebe. We’ve spent over a year delivering quality software to real clinics, growing to 1000+ users and selling enterprise contracts to multiple clinics.
I’ve also worked on enterprise software at IBM, and I’m excited to dive into a full-time SWE / AI SWE role starting January 2027 after I receive my bachelor’s degree in Computer Science.
Built automation that ports open-source software packages onto IBM’s Power servers, cutting porting time 70% per package.
Founded and built Kintec AI, an AI-powered physical therapy and recovery platform serving 1000+ users and signed to recurring contracts with 2 clinics, generating $6k+ revenue and improving patient adherence 30%; maintains a 5.0 App Store rating.
AI-powered physical therapy & recovery platform that guides patients through rehab programs. Serving 1000+ users and sold to 2 clinics, built end-to-end on a HIPAA-aligned AWS backbone.
Built at IBM’s ATX Bobathon: an enterprise document assistant that lets sales reps ask internal documents questions in plain English and get sourced answers mid-call. Adopted into production by IBM’s sales team.
Scores how trustworthy an open-source AI/ML model is, so engineering teams can decide in seconds whether it is safe to reuse. Python CLI over GitHub and Hugging Face Hub APIs with a weighted multi-metric scoring engine and 80%+ Pytest coverage.
Object-oriented casino simulation with 40+ classes (Blackjack, Poker, and more) built for clean architecture and easy extensibility.
20+ applied machine learning projects from IBM's AI Engineering specialization: supervised and unsupervised models, evaluation, and ML pipelines.
