I’m a software engineer who likes understanding how systems work under the hood. I focus on Backend Systems, Reverse Engineering, and Distributed Architecture.
In short: I break systems down to understand their mechanics, then rebuild them to run faster and more securely.
Right now, I’m a Software Engineer working on infrastructure that modern AI systems depend on. My long-term goal is to grow into a full-stack AI Engineer—someone who can architect an intelligent system end to end.
I’m following a structured roadmap:
- Phase 1 (Current Base): Deepening expertise in Distributed Systems, Backend Architecture, and SDE fundamentals.
- Phase 2 (Understanding the Data): Moving into Data Analytics & Data Science, because good models start with good data intuition.
- Phase 3 (Next Step): Machine Learning Engineering, bridging software engineering with probabilistic modeling.
- Phase 4 (The Goal): Full-stack AI Engineering—from data pipelines to models to deployment.
Languages
- TypeScript / JavaScript: My day-to-day. I use Bun.js for speed and Node.js for broader workloads.
- Python: For data tasks, AI pipelines, and quick scrapers.
- SQL: I take schema design and performance seriously.
Backend & Systems
- WebSockets: Heavy real-time use (e.g., in my DePulse project).
- Solana & Web3: Comfortable with on-chain state and Ed25519 signature flows.
- PostgreSQL & Redis: My preferred setup for storage, caching, and queues.
- Docker: Ensuring everything runs consistently, everywhere.
Architecture Patterns
- Onion Architecture: Keeping business logic clean and isolated.
- DePIN: Coordinating distributed physical infrastructure networks.
I’m currently digging into Kubernetes to strengthen my orchestration skills, and exploring Agentic AI workflows to understand how autonomous systems interact with the infrastructure I build.