Backend Engineer  ·  Cloud Infrastructure  ·  DevOps

I build systems that are meant to last — scalable, observable, and ruthlessly automated.

I'm a full-stack engineer with a clear bias: I live in the backend. From designing tightly-scoped APIs to wiring up distributed infrastructure, I care most about what happens after the request leaves the browser — how it's routed, validated, persisted, observed, and recovered when things go wrong.

My work sits at the intersection of backend engineering, automated testing, and cloud-native DevOps. I build pipelines that catch problems before they reach production, infrastructure that provisions itself, and services that tell you exactly what they're doing through metrics and traces. Reliability and velocity aren't a tradeoff — they're the same goal pursued with the right tooling.

I believe software is only as good as the systems that deploy, monitor, and protect it.

A full-stack AI marketing assistant built for small businesses and independent teams. It handles the entire campaign pipeline — from brief to copy to scheduling — so teams can focus on strategy instead of execution. Built with TypeScript and a modern web stack.

Documentation that writes itself. This tool analyzes a GitHub repository's structure, dependencies, and code patterns to generate architecture-aware docs that actually reflect how the system works — not just what the functions are named. Built with Python and ML-backed analysis.

A comprehensive healthcare expert system that handles complex, multi-part medical queries with structured, reliable outputs. Designed with care for accuracy and user trust. Built in JavaScript with intelligent query routing.

A browser-based code editor with real autocomplete, live error detection, and automatic fix suggestions — not just syntax highlighting. Supports guest sessions and persistent project management. Built in JavaScript.

A real-time cross-platform chat application, mobile-first by design. Built with Flutter/Dart for consistent behaviour across Android and iOS without maintaining two codebases.

Backend & APIs — Express, FastAPI, Flask, Spring Boot (Maven)
Cloud Infrastructure — AWS, GCP, Terraform (infrastructure as code, not afterthought)
Containers & Orchestration — Docker, Kubernetes
CI/CD — GitHub Actions, Jenkins
Observability — Prometheus for metrics collection, Grafana for dashboards and alerting
Testing — Pytest, Jest, Playwright, React Testing Library
Databases — MongoDB, PostgreSQL
AI/ML — CrewAI, LangChain, Scikit-learn, TensorFlow, Pandas, NumPy
Frontend — Next.js, React, Flutter

A service isn't done when it deploys. It's done when you can tell — at a glance, from a Grafana dashboard — whether it's healthy, where it's slow, and what broke last Tuesday at 2am. I instrument everything I build with Prometheus metrics and pipe them into Grafana so that observability is a feature, not an incident-response tool.

The same principle applies to testing and CI. A pipeline that lets broken code through isn't a pipeline — it's a false sense of security. I write tests that catch real failures, configure gates that enforce them, and build deployment workflows where confidence is earned, not assumed.

• Microservices with Spring Boot, containerized and orchestrated on Kubernetes
• Full observability stacks: Prometheus scraping + Grafana alerting on custom dashboards
• Terraform modules for reproducible, version-controlled cloud environments
• Exploring serverless-first patterns for event-driven workloads on AWS and GCP

"Design. Build. Automate. Scale."