I'm a software engineer who lives at the intersection of backend systems, cloud infrastructure, and artificial intelligence. I care deeply about building things that are robust, observable, and elegant under the hood — not just on the surface.
From designing resilient microservices and CI/CD pipelines to training and deploying ML models at scale, I enjoy the full spectrum of turning ideas into production-grade systems. My philosophy is simple: great software is built with intention, tested with rigor, and shipped with confidence.
A curated stack built over years of hands-on engineering across backend, DevOps, and AI.
A selection of projects that reflect how I think about engineering problems.
A production RAG pipeline that ingests enterprise documents and serves intelligent answers through a conversational API — deployed on Kubernetes with auto-scaling inference.
View Project →A self-healing infrastructure platform that manages multi-cloud deployments with automated failover and cost optimization.
View Project →End-to-end MLOps pipeline with automated training, versioning, A/B testing, and canary deployments for production ML models.
View Project →A high-throughput authentication microservice handling 10K+ req/s with event sourcing, rate limiting, and distributed session management.
View Project →