Dan Podina · Software architect
I’m Dan Podina. I help teams make sense of their backends, integrations, and the path from a working prototype to a system they can depend on. My experience spans fintech, healthcare, and SaaS — from trading infrastructure to clinical data platforms and a Go-based low-code framework.
Cluj-Napoca, Romania · Building software since 2005
Make backend and integration decisions with the whole system in view: service boundaries, data ownership, reliability, and the cost of operating what you build.
Through SystemTrails, I help founders prepare for real users, enterprise pilots, due diligence, and growth with architecture reviews, hardening, and senior oversight.
Experience behind the advice
2024–2026 · Ikon Soft
Architected and led development of a cloud-native clinical trials data platform for Quest Diagnostics. Designed event-driven microservices on AWS and GCP, real-time data pipelines, and HIPAA-compliant infrastructure.
2018–2024 · Ikon Soft
Designed and built BGASOFT — a low-code rapid application development framework in Go. Multi-tenant SaaS architecture, code generation engine, visual workflow builder, and plugin system.
2005–2010 · NOVA INVEST
Maintained and operated trading systems infrastructure for a financial services firm. Server administration, deployment automation, monitoring, backup and disaster recovery.
Notes on building systems and working with AI, grounded in the decisions behind the code.
Architecture patterns get the attention. What decides how a project goes is gathering information, clarity, staying organized, and people.
Choose service boundaries using deployment needs, ownership, consistency, and operating costs. A worked example shows when a separate worker is enough.
A practical architecture review for AI-built backends, following one request through authorization, tenant data, retries, background jobs, and recovery.
A backend that has outgrown its first design, an integration that keeps breaking, or an AI-built product facing its first serious users: start with the problem and the constraints.
Clean boundaries. Honest abstractions.