Tech Lead | Product Architecture | AI & Distributed Systems
I design and evolve product systems under real constraints — balancing architecture, delivery, reliability, and long-term maintainability.
I'm a Tech Lead with experience designing and evolving backend systems and digital products across healthcare, browser products, and web-scale data workflows. My work sits at the intersection of product architecture, technical direction, and reliable delivery. I'm especially interested in systems that need to balance product constraints, operational simplicity, and long-term evolution.
I'm especially interested in product environments where architecture is shaped by real constraints: evolving requirements, operational complexity, reliability, and long-term maintainability.
Leading the technical evolution of a high-usage web crawling product used daily by thousands of customers. Focused on architecture, reliability, observability, execution consistency, and AI-assisted engineering workflows in a lean product team.
Led the evolution of a browser extension product for automated consent management. Defined architecture under strong technical constraints, guided delivery and engineering quality, and translated business needs into a sustainable product direction.
Owned a healthcare automation platform end-to-end, from requirements and client interaction to architecture, AWS infrastructure, data modeling, and delivery. Acted as the main technical counterpart for stakeholders and led engineering execution around security, scalability, and maintainability.
Contributed to the evolution of a monolithic platform into a microservices architecture across roughly 10 services. Improved modularity, modernized the backend stack with TypeScript and NestJS, and helped raise engineering standards through shared libraries, mentoring, and internal tech talks.
Worked on research and innovation projects across AI, IoT, and blockchain. Built internal tools and web applications across frontend and backend, applying solid engineering practices in exploratory environments.
Provided IT support for retail POS systems and automated repetitive support tasks with scripts.
A manual, spreadsheet-heavy healthcare operations workflow that was fragile, error-prone, and couldn't scale.
End-to-end ownership with no existing platform foundation, strong compliance and data security requirements, direct client dependency.
Designed a purpose-built platform from scratch — full technical ownership across requirements, AWS infrastructure, data modeling, and delivery. Kept the architecture simple enough to be maintainable by a small team.
Eliminated a category of operational errors and replaced a fragile process with a system the client could actually scale.
Evolving a browser extension for automated consent management under strict and shifting platform constraints.
Browser extension environment imposes hard limits: CSP rules, limited storage, cross-browser compatibility, no access to native APIs. Short-term delivery pressure alongside long-term product evolution.
Defined a maintainable architecture with clear separation of concerns. Prioritized extension longevity over feature velocity — keeping the core stable while enabling product iteration on top.
Team of 5 delivered a sustainable product direction within tight constraints, with architecture that could absorb platform changes without full rewrites.
Integrating AI meaningfully into a production crawling system used daily by thousands of customers — without compromising reliability or adding operational overhead.
Lean team, high usage volume, need for consistency and observability in AI-driven flows. AI features had to be reliable, not experimental.
Introduced LLM-based workflows and RAG systems designed around real user flows and operational constraints. Also applied AI-assisted engineering to reduce repetitive internal work.
Enabled AI-powered product capabilities with production-grade reliability, and improved internal delivery throughput in a lean team.
I'm most interested in roles where architecture, product constraints, and system evolution matter more than hype.