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Jan 22, 2026
Intro 101
Systems Engineer / Polyglot Builder
I build backend-heavy systems where reliability, performance, and failure modes actually matter, especially under real load.
Trading systems, real-time apps, AI pipelines, and polyglot backends.
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My work spans frontend, backend, data, and infrastructure, but my center of gravity is backend systems.
Most of my serious work lives in private repositories or production systems.
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Real-time chat system designed for high concurrency and low latency. WebSocket connection setup ~100µs. Go for network IO, Elixir/Phoenix for orchestration, SolidJS frontend.
E-commerce platform with product catalog, cart management, and checkout flow. Built with modern web stack focusing on performance and user experience. JavaScript.
Audio-to-subtitle pipeline using Faster-Whisper for speech recognition. GPU-accelerated processing on Kaggle. Handles multiple languages with quality enhancement. Python, FFmpeg.
Production systems under NDA involving trading automation, data pipelines, and infrastructure. Details available on request.
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Over time, I've worked across many layers of the stack. I choose tools based on constraints, not trends.
I don't just build web views. I build native clients when performance or OS integration matters.
Web: SolidJS, React, Vue.js
Mobile: Flutter, Kotlin Multiplatform (KMP)
Desktop: C++ (Cross-platform), C# (Native Windows)
Most of my work lives here , services that handle concurrency, real traffic, and failure modes.
Rust, Go, Elixir (Phoenix), Node.js, Python
I've worked with both transactional and analytical workloads, choosing stores based on access patterns and scale.
PostgreSQL, Redis, SQLite, Message Queues, File-based pipelines
I build AI-powered systems that solve real problems: speech recognition pipelines, trading bots with ML-driven strategies, and data analysis for production decisions.
Python (with its vast ML ecosystem), Kaggle (for GPU access)
I care about repeatability, observability, and knowing how systems fail.
Linux, Docker, CI pipelines, Cloud deployments
Tools change. Principles don't.
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I optimize for long-term system health, not short-term cleverness.
I use AI to accelerate implementation, not to replace judgment.
I write tests and simulations because production always finds edge cases.
I value readability first, performance second, cleverness last.
I ship incrementally and measure before optimizing.
I document decisions so future me (or teammates) can reason about them.