Interdisciplinary Software Engineer based in United States.
I build thoughtful, design-first products.
Currently focused on Applied AI and ML research.
Founding Engineer at SportTriad
SWE + Product Design at American Completion Tools
AI Researcher at University of Kansas
Software Engineer at Cybronical Tech
Founding AI Engineer — product and platform.
Triad is an early-stage platform focused on the mental and emotional development of young athletes. It helps players, parents, and coaches build healthier habits around confidence, reflection, and communication — not just performance.
Triad is designed around a privacy-first knowledge graph that models relationships between athletes, reflections, habits, and contextual signals over time, rather than relying on raw conversational history. Sensitive data is stored as structured, permissioned nodes with explicit ownership and visibility rules across athlete, parent, and coach roles. The knowledge graph enables longitudinal insight and personalization while minimizing data exposure, and AI systems operate only on scoped, derived representations rather than direct access to raw user content. This architecture emphasizes auditability, least-privilege access, and long-term trust, which are critical when building systems for youth users.
Co-founding team — product research, product design, and UX.
Sporttriad is the company behind Triad. As part of the founding team, I led product research to understand how young athletes, parents, and coaches actually talk about stress, confidence, and performance. This meant running interviews and lightweight discovery sessions, mapping out the emotional journey around games and training, and turning those narratives into specific opportunities for the product to help.
On the product design side, I owned the end-to-end UX for our first releases: onboarding, daily check-ins, insights, and coach dashboards. I worked from low-fidelity flows to detailed UI, creating a design system that balanced a calm, trustworthy aesthetic with clear affordances for logging feelings, reflecting on patterns, and taking action. Every interaction was designed to feel supportive rather than clinical, especially for younger athletes who might be opening up about difficult topics for the first time.
Beyond the UI, I helped define how Sporttriad ran experiments: what to ship first, how to measure whether a feature actually reduced friction or improved reflection habits, and how to keep the system technically simple while still supporting future AI-assisted experiences. Day to day, this looked like an ongoing loop between user research, product strategy, IA and interaction design, and hands-on implementation in collaboration with engineering.
Software Engineer + Product Designer
At ACT, I built and deployed an internal ERP system to support HR, payroll, onboarding, and vendor coordination. The system replaced spreadsheets and manual tracking with a centralized platform that processes over $250K annually in payroll and reduced administrative overhead by 40 percent. The focus was reliability and clarity. The team needed software they could trust every day.
I owned the full stack. I designed the PostgreSQL schema with clean relational models and constraints to maintain data integrity. I built REST APIs in Node and Express to handle payroll transactions, document management, and vendor workflows. On the frontend, I developed responsive React interfaces that simplified complex operational flows into usable dashboards. I also implemented role based access control, audit logging, and AWS EC2 and S3 backed storage to make the system secure and production ready.
Most of the work involved sitting with operations and finance teams, understanding how work actually moved through the company, and turning that into structured systems. I shipped incrementally, gathered feedback directly from users, and improved performance and usability with each release. It was practical engineering in a real production environment, focused on impact over perfection.
Vision assistance and accessibility platform.
Vissionassist is a vision assistance and accessibility platform designed to help users with visual impairments navigate digital content more effectively.
Frontend Engineer + AI
Marketise.ai is an AI-driven marketing platform that helps brands analyze, optimize, and create digital presence assets by leveraging machine learning and automated workflows. Built with scalable backend services and modular AI components, the system ingests brand profiles or URLs and produces structured insights about visual identity, messaging, and aesthetic cues that can inform design and content decisions. By transforming raw brand inputs into semantic metadata and recommendations, Marketise.ai reduces manual research effort and enables rapid iteration on brand-centric campaigns and communication strategies.
In my role working on Marketise.ai, I contributed to the end-to-end development of core platform features spanning data ingestion, AI inference pipelines, and responsive front-end interfaces. This involved building secure APIs for processing user inputs, integrating third-party models for brand analysis and semantic extraction, and optimizing performance for real-time feedback loops. I also worked on architecture improvements to support maintainability and horizontal scalability as usage grows, with a strong focus on modular service design and observability in production.
Advanced scheduling and appointment management system.
An advanced scheduling and appointment management system designed for efficient time management and booking workflows.
Product design | UI/UX
I designed a scouting dashboard focused on helping users quickly understand player information without cognitive overload. The work was driven by user research and regular feedback from scouts to understand how they scan data, what they trust visually, and where friction exists in existing tools. The goal was to surface the right information at the right moment, reducing unnecessary complexity while keeping depth accessible when needed.
From a design perspective, I focused on clear information hierarchy, consistent spacing, and readable typography to support fast decision-making. Layouts and components were designed and iterated in Figma, with attention to alignment, color usage, and interaction states across different screen sizes. The final UI emphasizes clarity, consistency, and usability, ensuring the dashboard feels intuitive and reliable in real scouting workflows.
