Backend
Engineer

I architect systems that scale. From distributed databases to high-frequency trading enginesβ€”building the invisible infrastructure that powers digital experiences.

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backend_systems.rs
$ cargo run --release
Compiling backend_systems v1.0.0
Finished release [optimized] target(s)
Running `target/release/backend_systems`
[INFO] Initializing distributed system...
[INFO] Kafka cluster: 3 brokers online
[INFO] Database pool: Ready (50 connections)
[INFO] Health check endpoint listening on :8080
[INFO] System ready. Processing events...
$

System Architecture

⚑
Load Balancer
HAProxy + NGINX
99.99% uptime guaranteed
πŸ”„
API Gateway
Rate limiting, auth, routing
Sub-millisecond latency
🧠
Microservices
Containerized, auto-scaling
Independent deployments
πŸ“Š
Message Queue
Apache Kafka cluster
Million events/sec
πŸ’Ύ
Database Layer
Sharded PostgreSQL
Real-time replication
πŸ“ˆ
Monitoring
Prometheus + Grafana
Real-time observability

Programming Languages

Rust
4 Years
Go
6 Years
Python
8 Years
C++
5 Years
Java
7 Years
TypeScript
5 Years
Elixir
3 Years
Zig
2 Years
"The best backend is the one you never think about. It just works, scales infinitely, and degrades gracefully."
β€” Backend Philosophy

My Approach

I don't just write codeβ€”I solve problems. Every system I build starts with understanding the constraints: latency requirements, throughput demands, consistency guarantees.

fn build_system() -> Result<System> {
// Start with the constraints
let latency = "sub_millisecond";
let throughput = "millions_per_second";
}

Whether it's a sub-millisecond trading engine or a distributed event streaming platform, I focus on the fundamentals: proper data structures, efficient algorithms, and system design that anticipates failure.


The best solutions are often the simplest ones. Complexity is the enemy of reliability.