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The story

From body signals to machine signals

Senior Android & Flutter engineer building mobile products, payment systems, and hardware-connected experiences.

The biomedical mindset

Signals don't negotiate

Where the reliability mindset comes from.

My degree is in biomedical engineering. The curriculum was instrumentation and systems: how to measure a signal without distorting it, how to know when a reading can be trusted, and what happens when a device fails while someone is depending on it.

I don't work in that field anymore, but it set the defaults I still build with. Read the specification before the tutorial. Trust measurement over opinion. Treat failure modes as part of the design, not as edge cases to patch later.

The move to software

Sensors became screens

The same engineering thinking, applied to a new class of systems.

Moving into software in 2020 wasn't a career reset — it was the same engineering, pointed at different systems. Android first: screens, then state management, then the architecture underneath them — clean boundaries, predictable state, codebases that stay cheap to change as the team and the product grow.

Production work raised the bar in ways I wanted. FinTech and payment systems, where correctness is measured in money. Then hardware communication — MDB over serial, NFC, AIDL — where the app is the controller of a physical machine. Different domain, same rule I learned from instrumentation: the system tells you what's happening; your job is to read it correctly and design for the day it misbehaves.

Engineering × craft × product

Owning the outcome

Complete products — architecture, experience, reliability.

At some point the job stopped being "write the code" and became "own the outcome". Today I think in complete products: the architecture, the user experience, the reliability envelope, and the business constraints that shape all three. Two of those products are my own, in production with real users — a multi-tenant inventory platform and a cross-platform media player. Owning what you ship changes how you write it: maintainability stops being a virtue and becomes survival.

AI is an engineering multiplier, and I use it as one — to accelerate development, improve workflows, and explore product directions that wouldn't have justified the time before. The standards don't move: architecture is still written down, changes are still reviewed, reliability is still non-negotiable. AI raises the speed. The discipline decides the quality.

Timeline

  • 2017

    Biomedical Engineering

    Instrumentation, signals, and systems — the foundation.

  • 2020

    Software Engineering Transition

    Same engineering thinking, new medium.

  • 2020 — 2023

    Android & Flutter Development

    From first apps to production codebases.

  • 2023 — 2024

    Senior Mobile Engineering

    Architecture ownership, production at scale.

  • 2024 — 2026

    FinTech, Payment Systems & Hardware Integration

    Payment platforms for machines — MDB, NFC, serial.

  • 2025 — Present

    AI-assisted Product Development

    Complete products, built with AI in the workflow.

See the workHow I build