I design cloud-native data platforms, backend systems, and AI-focused products with a strong emphasis on reliability, performance, and business impact.
I work across data engineering, backend development, cloud platforms, and AI-oriented product building. My portfolio highlights practical systems that are designed to be scalable, dependable, and business-ready.
Clean systems, maintainable code, strong structure, and recruiter-friendly presentation.
Every project is framed around practical use, measurable value, and architecture clarity.
Built to deploy smoothly on GitHub Pages without depending on fragile live APIs.
These cards are static by design so the site remains fast and reliable on every load.
A cloud-based AMS platform focused on policy workflows, agency operations, CRM, and AI-assisted productivity.
A practical framework for AI evaluation, policy alignment, observability, and governance-focused workflows.
An experimental fraud detection project exploring hybrid ML concepts and quantum feature maps.
A reliability-focused project centered on freshness checks, monitoring patterns, and operational health.
This section avoids GitHub API calls, so it works consistently on GitHub Pages without rate-limit issues.
Enterprise AI governance, observability, and evaluation workflows.
Quantum experimentation for fraud detection with research-style implementation.
Reliability-focused monitoring patterns for modern data platforms.
Showcase your technical writing, books, and newsletter presence in one place.
Technical articles, system design writing, and portfolio visibility.
Newsletter publishing and recurring thought leadership.
Published work that strengthens your portfolio and authorship profile.
I’m open to roles, collaborations, and conversations around data engineering, AI systems, and cloud platforms.