Clear goals. Relentless execution. Daily reflection. That’s how I compound progress.
Turning complex ideas into real, working AI products — and refining the system behind every outcome.
I am an AI Solutions Architect and software engineer with end to end experience, focused on turning vague ideas and scattered requirements into systems and products that ship. To me, engineering is not about showing off complexity. It is about clarifying the problem, making solid tradeoffs, and delivering outcomes people can rely on.
In projects and product work, I often play the role of a translator and integrator. I can go deep on architecture, data flows, performance, and reliability with engineering teams, while also aligning with product partners and customers on goals and real constraints. My value is not only building features, but building the right thing in the right way, so it gets adopted, maintained, and scaled.
I believe strong engineers do more than write code. They make alignment clear, keep risks visible, and make delivery predictable. Technical skill sets the ceiling, communication sets the direction, and disciplined iteration turns each release into lasting momentum.
Right now, I am continuing to sharpen my skills in AI system engineering and hardware software integration while pursuing a Master’s degree in Electrical and Computer Engineering in the United States. I enjoy making complex problems simpler and more reliable, and I care about building AI that earns trust in real world use.
Specializing in AI systems where hardware constraints shape model design. Focused on reliability, efficiency, and deployment-aware tradeoffs across data and system architecture.
Computer engineering track emphasizing software systems and applied ML. Built a strong foundation in communications, signals, and systems alongside rigorous programming.
After my promotion, I took on the role of lead engineer and product owner to deliver an enterprise AI agent platform from concept to production. I did not only plan and coordinate. I personally built key parts of the core system, including LLM workflows, the knowledge base and RAG pipeline, inference strategy, backend architecture, and cloud deployment. The goal was clear: ship a platform that enterprises can adopt, operate, and scale, and that drives real business outcomes.
As an AI Software Engineer, I focused on NLP and LLM engineering, model training, and production delivery. I connected research with real systems by turning models into reliable services and shipping features that were used in day to day enterprise workflows.
Volunteered as a mentor for OSU AI PhD applicants, helping sharpen research positioning and application materials through focused CV and essay reviews.
Selected to design and teach an internal applied AI course, running hands on sessions to help colleagues use AI methods in real workflows.