I architect production-grade cloud infrastructure and design high-performance backend systems. Driven by rigorous algorithmic problem-solving, I specialize in writing highly efficient, low-latency code for scalable, distributed environments.
- Performance & Algorithmic Optimization: Applying competitive programming (Codeforces) principles and advanced DSA to write highly efficient, low-overhead code for complex systems.
- Cloud Architecture: Designing highly available, fault-tolerant infrastructure on AWS (EC2, ECS, ASG, ALB).
- Infrastructure & Automation: Building optimized Docker deployment pipelines and managing containerized workloads.
- Site Reliability: Engineering robust observability flows and low-latency system optimizations.
- Open Source: Actively contributing to modern deployment platforms and DevOps tooling.
| Category | Technologies |
|---|---|
| Languages & Core | C++ (Advanced DSA), TypeScript, Python, Java |
| Cloud & DevOps | AWS (EC2, ECS, ASG, ALB, SQS), Docker, Kubernetes, Linux, Nginx, CI/CD |
| Backend & APIs | Node.js, Express.js, REST, WebSockets, Prisma |
| Databases | PostgreSQL, MongoDB |
| Observability | Prometheus, Grafana, New Relic |
Dokploy (Deployment Platform / PaaS)
- Engineered configurable Node.js versioning within the Docker build system, expanding developer flexibility for containerized environments.
- Integrated native support for Node 25, modernizing runtime compatibility across the platform.
Site Reliability Engineering initiative for distributed systems.
- Architected a system focused on scaling cloud reliability through cognitive compression and distributed routing.
- Optimized infrastructure performance and backend fault tolerance.
OpenEnv-compliant Reinforcement Learning Environment.
- Engineered an agent-based simulation with complex reward optimization for environmental decision-making.
- Achievement: Grand Finalist at the Meta PyTorch OpenEnv Hackathon (Ranked among top teams out of 52,000+ developers).
Platform for evaluating predictive models.
- Built a comprehensive pipeline to detect, measure, explain, and automatically mitigate hidden algorithmic bias in real-time.
