Backend & Distributed Systems Engineer
Production-grade Systems • Go • Bun • Zig • DevOps

Building scalable, high-performance backend systems with a focus on clean architecture and operational excellence.

Embedded, Cross-Platform Graph Database with WebAssembly Query Engine

A modular, production-grade graph database platform with a custom binary storage engine, WASM-powered query processor, and full-stack management interface.

• Custom binary graph storage with Memory-Mapped I/O
• Write-Ahead Logging (WAL) for durability
• Segmented Storage architecture
• ARC Cache + Bloom Filter for performance
• Hash Indexing & Memory Pool optimization
• gRPC interface with Structured Logging

• Independent query engine compiled to WebAssembly
• Layered architecture:
  • Lexer → Parser → AST → Semantic Analysis → Query Planner
• SQL-like query language support
• Optimized execution planning

• Snapshot & Backup Manager for data recovery
• Nuitka compilation to standalone executable
• Free-Dependency deployment (no Python runtime required)
• Exposed as Tauri Sidecar for seamless integration

• Analytics Dashboards for real-time insights
• Graph Studio for query writing and execution
• Community Detection algorithms
• React Flow interactive graph visualization
• Viewport-Based Fetching (Google Maps-style progressive loading)
• Interactive documentation for graph algorithms and data structures

• Rust-based performance benchmarking framework
• Zig implementations for algorithm optimization
• Native library with C Extension + C ABI
• Python bindings for seamless integration
• Cross-algorithm performance comparison

• Docker Compose for local development
• Kubernetes for production orchestration
• Full CI/CD pipeline with automated testing and deployment

• ✅ Cross-Platform (Windows & Linux)
• ✅ Embedded - No external dependencies
• ✅ High Performance with memory-mapped I/O
• ✅ SQL-like Query Language via WASM
• ✅ Interactive Graph Visualization with React Flow
• ✅ Production-Ready with full CI/CD

• Distributed Systems – Building resilient, scalable microservices • High-Performance Computing – Optimizing for throughput and latency • Graph Databases – Efficient storage and querying of connected data • Microservices – Domain-driven design and service orchestration • Clean Architecture – Separation of concerns and maintainability • DevOps & Platform Engineering – CI/CD, observability, and infrastructure as code

• Clean Architecture & Code Standards – Separation of concerns, modularity, and clean, maintainable code that stands the test of time

• Scalability & Reliability – Fault-tolerant services with horizontal scalability and sustainable growth, not short-term fixes

• Performance Optimization – Query optimization, latency reduction, and eliminating architectural bottlenecks

• Engineering Quality & Testability – Systematic debugging, thorough testing, and proactive monitoring for production reliability

• End-to-End DevOps Mindset – Full ownership from design and deployment to monitoring and continuous improvement

• Collaborative Professionalism – Clear communication, constructive code reviews, proper documentation, and agile team collaboration

• Continuous Learning – Applying cutting-edge tools and modern architectural patterns to practical, production-ready solutions

I thrive in challenging environments where engineering rigor, performance, and scalability are paramount, solving complex problems with elegant, maintainable solutions.

• Kubernetes – Advanced orchestration and operator patterns
• SRE Practices – Service Level Objectives, error budgets, and incident management
• System Design – Large-scale distributed architectures
• Linux Internals – Kernel, processes, memory management, and I/O
• WebAssembly – High-performance browser and edge computing
• Distributed Databases – Consistency models, sharding, and replication strategies

💡 "Building systems that are not just functional, but elegant, scalable, and resilient."