I'm a software engineer focused on AI systems, developer tools, and production web products.
I like building software that has a clear product surface and a real technical core — desktop tooling, AI-assisted workflows, career intelligence, applied machine learning, backend systems, and scalable web applications.
My current work sits at the intersection of software engineering + AI + developer experience.
- Building an AI-native desktop editor with Tauri, Rust, React, and Monaco
- Building AI-driven career and interview workflows with Next.js, Node.js, and TypeScript
- Working with Python, FastAPI, Django, ML pipelines, and data systems
- Experienced with Salesforce, Apex, LWC, Flows, and enterprise application development
- Interested in local-first software, intelligent developer tooling, agents, and applied AI
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Local-first AI-native code editor A desktop coding environment built with Tauri, Rust, React, TypeScript, and Monaco. Veyra combines native project access, Git, a real terminal, installable themes/snippets, and multi-provider AI workflows with reviewed edits. Stack: Tauri · Rust · React · TypeScript · Monaco |
AI career intelligence platform A production-oriented platform for live jobs, resume intelligence, ATS analysis, evidence-based matching, interview practice, skill-gap discovery, and application tracking. Stack: Next.js · TypeScript · Node.js · Express · AI |
| Project | What it explores | Core stack |
|---|---|---|
| Veyra Editor | Local-first AI coding environment, desktop tooling, reviewed AI edits | Tauri, Rust, React, TypeScript, Monaco |
| CareerFit | Career intelligence, job ingestion, resume analysis, AI interviews | Next.js, Node.js, TypeScript |
| IntelliThesis | AI-assisted research and thesis workflows | Next.js, Express, FastAPI, MongoDB |
| High Contrast Subspaces / Outlier Ranking | Density-based anomaly detection and outlier analysis | Python, pandas, NumPy, scikit-learn |
| CryptoTrack | Realtime/historical crypto data pipelines and dashboards | React, Node.js, PostgreSQL, EC2 |
| Neurolumina | LLM interaction and model-training experimentation | TypeScript, Python, FastAPI |
understand the problem
↓
design the smallest useful system
↓
build the core workflow
↓
measure what actually works
↓
ship → learn → improve
I care about product usefulness, clean architecture, developer experience, and actually finishing the build.