Backend & Distributed Systems Engineer | Microservices | DevOps | Production-Grade | Ex-Military Precision
I design and build secure, scalable, and high-performance backend systems with a focus on correctness, observability, and reliability.
- 🐍 Backend: Python (Django/DRF), PHP (Laravel), Rust for performance-critical services
- 🔒 Security-first: environment-based secrets, ORM-safe queries, API rate limiting, hardened configs
- 🧠 Systems thinking: protocols, configuration design, benchmarking, failure-mode analysis
- 🛠️ DevOps automation: CI/CD pipelines, Docker, reproducible environments, cloud deployments
- ⚡ Frontend (when needed): Vue.js, TailwindCSS — strict separation of concerns
- 🎖️ Discipline-driven: military-inspired approach for deliberate, precise engineering
Concurrent TCP String Lookup Server (Systems & Performance Engineering)
Recently built a production-style concurrent TCP server with:
- Multi-threaded request handling
- TLS support (config-driven certificate & key paths)
- Config-based behavior (no hardcoded paths, environment-driven config loading)
- Multiple search strategies (
set,sorted,scan,splitlines,grep) - Benchmarking harness with p99 / max latency and reproducible runs
- ~2,400+ lines of tests for branch/edge-case coverage
- Static analysis with Bandit, Ruff, MyPy and 0 medium/high severity issues in application code
This project reflects how I approach backend work: spec → design → implementation → tests → benchmarks → security → documentation.
Microservices Platform (Rust + Python) — Production-Grade Backend Systems Designed and deployed modular microservices integrating Python (Django/DRF) and Rust (Actix/Axum)
- Secure APIs with JWT/OAuth2, rate-limiting, and environment-driven configuration
- Distributed architecture supporting high throughput and fault-tolerant workloads
- Observability-first design: structured logging, metrics, and failure-mode monitoring
- Automated CI/CD pipelines and cloud deployment workflows for reproducible production environments
- Benchmarked services for performance, latency, and reliability, ensuring global production standards
- Enabled AI/LLM-backed services integration for dynamic backend processing
This highlights my approach: modular design → secure implementation → observability → CI/CD → performance → AI integration → production-ready delivery.
- Designing and deploying modular microservices (Rust + Python) with secure, observable, and scalable APIs
- Building distributed backend systems for high-performance, fault-tolerant workloads
- Implementing production-grade CI/CD pipelines and automated cloud infrastructure workflows
- Integrating AI/LLM-backed services into backend systems for dynamic decision-making
- Enforcing robust API security, authentication, and rate-limiting across all services
- Exploring high-performance Python patterns and observability-driven optimizations
| Backend & APIs | DevOps & CI/CD | Frontend | Security & Quality |
|---|---|---|---|
| Python (Django, DRF) | Docker, Docker Compose | Vue.js, TailwindCSS | Bandit, Ruff, MyPy |
| PHP (Laravel, Sanctum) | GitHub Actions, CI pipelines | Pint, Larastan, PHPStan | |
| REST APIs, JWT, OAuth2 | Pre-commit hooks, Automation | Env-based secrets, CORS, ACLs | |
| PostgreSQL, MySQL, SQLite | Cloud deployments (AWS/GCP) | API rate limiting & logging |
I use pinned repositories to showcase systems-level backend projects, performance-focused services, and secure API backends.
Discipline, clarity, and precision — in code and in life.