With a passion for clean architecture and a love for solving complex backend challenges, I specialize in turning raw ideas into fast, reliable, and scalable systems. From early prototypes to production-ready infrastructures — I’ve done it all, and I’m just getting started.

I'm a full-time backend developer focused on building clean, scalable, and intelligent systems.
Whether it's machine learning, automation, or real-time data pipelines —
I help ideas turn into working, reliable, and future-ready systems.

🚀 What I Do
- 🧩 Craft modular, readable, and production-grade backends  
- 🔁 Design dynamic pipelines for multi-model inference  
- 🧠 Build smart logic with memory, state-awareness, and fallbacks  
- ⚙️ Automate everything from data ingestion to real-time decisions
- 🛠️ Tech doesn't drive my decisions — the product does. I pick tools that fit the problem, not the trend.
    
I don’t just wire things up — I make sure they think, respond, and scale.

Over the years, I’ve worked across different industries—each one throwing a unique set of challenges at the backend. Some needed speed, some needed flexibility, and some just needed someone who could make sense of chaos. I’ve seen APIs disappear overnight, models change without warning, and data that made no sense — and I’ve grown to love that kind of unpredictability. 🧑‍💻 Freelancing taught me how to take ownership and deliver without waiting for permission 🚀 Startups taught me how to build fast, stay flexible, and think beyond just code 🛰️ Research labs taught me how to work with uncertain data and long-term impact in mind Right now, I'm focused on building backends for AI-powered systems — where the logic needs to evolve just like the data it's built on.

Streaming is chaos with a clock ticking. Supporting real-time data flows, handling RTSP protocols, and ensuring compatibility across native browsers and devices means you’re constantly firefighting — buffering, dropping, re-connecting. The challenge is building a system that just works — whether it's for a camera on a factory floor or someone watching on a low-end mobile device.

Working with large language models, especially in multi-agent orchestration setups, brings a different kind of complexity. Models are async, responses are fuzzy, and memory matters. You’re not just handling API calls — you’re coordinating thought processes. Whether it’s routing requests, managing context, or dynamically adapting the system logic, backend work here feels more like building a brain than a pipeline.

This space moves fast — models change, formats shift, and what worked yesterday might not work tomorrow. I’ve worked on backends that had to stay flexible, because the people using them were still figuring out what exactly they needed. The biggest challenge wasn’t scale — it was staying adaptable without losing stability.

Here, the main problem is control. Most platforms don’t give you APIs, and when they do, they’re incomplete or unreliable. You end up dealing with messy data, unpredictable flows, and the constant need to sync everything without breaking. It’s a game of consistency in a world that doesn’t want to be consistent.

This world is all about speed and responsiveness. Users expect real-time performance, even when content is constantly changing and traffic is unpredictable. The challenge here isn’t just delivering fast—it’s doing that while keeping everything clean, secure, and easy to manage behind the scenes.

Working with research teams and satellite data is a different rhythm altogether. It’s less about speed and more about precision. The data is huge, the formats are complex, and the value often lies in the tiniest detail. It’s slow, thoughtful work — and it teaches you how to handle uncertainty with structure.

I enjoy being where things are messy, undefined, and evolving. That’s where backend work really starts to matter.

That said, I’d love to talk about what I’ve built and even more so, learn what others are building because listening, sharing, and geeking out together might just be my second-best skill. 😄