Full-stack engineer working on search infrastructure, data pipelines, and AI systems in the automotive aftermarket.
I build software that runs at scale: search infrastructure behind hundreds of e-commerce sites, databases holding hundreds of millions of rows, and AI systems built for production rather than demos. Most of my work sits at the intersection of hard data problems and infrastructure that cannot go down.
Search at scale. Design and operation of self-hosted search infrastructure serving hundreds of production e-commerce sites: index architecture, caching strategy, and load testing to sub-15ms hot p95 latency.
Automotive data standards. Deep expertise in ACES and PIES (VCDB, PCdb, PAdb, Qdb), fitment architecture, and the data modeling problems unique to the aftermarket. Author of an open-source ACES 4.2 validator built in Rust with DuckDB and SARIF output.
AI infrastructure. Building internal AI platforms and MCP servers that connect LLM tooling to production data systems, with the auth, policy, and cost controls that requires.
Databases under load. MariaDB at scale: query optimization, schema design, ingestion pipeline tuning, and diagnosing the failure modes that only show up in production.
| Project | Description |
|---|---|
| ACES 4.2 Validator | Open-source validation tooling for ACES XML. Rust, DuckDB, SARIF output for CI integration. |
| Nebula | A statically typed language for AI agent authoring that compiles to Python. Compiler written in Rust. |
Languages: TypeScript, Python, PHP, Rust, SQL Data: MariaDB/MySQL, Redis, DuckDB, Meilisearch, Algolia Backend: Node.js, FastAPI, FastMCP, CodeIgniter Infrastructure: GCP, Plesk, Docker, Linux server administration
Open to conversations about search infrastructure, aftermarket data standards, and AI tooling.