Java • Spring Boot • Kafka • Kubernetes • Observability • AI/MCP
I build backend services, event-driven systems, and cloud-native applications. I’m currently exploring practical AI engineering through MCP, developer automation, and AI-assisted open-source contribution workflows.
- 🔭 Currently working on Kafka, MCP, and developer automation
- 🌱 Exploring applied AI for backend and platform engineering
- ✍️ Sharing what I learn through technical articles
- 💼 Open to Backend and Platform Engineering opportunities
- 🔗 Connect with me on LinkedIn
- Backend: Java, Spring Boot, REST APIs, microservices
- Event-driven systems: Apache Kafka, asynchronous workflows
- Cloud-native engineering: Docker, Kubernetes, Istio
- Observability: Prometheus, Grafana, Spring Boot Actuator
- Applied AI: MCP servers, AI-assisted developer tooling
A practical Kafka learning and reference workspace containing Java and Python examples, Docker-based infrastructure, and planned real-world streaming applications.
Experiments and tooling for building MCP servers with Python, FastMCP, uv,
and the MCP Inspector.
A pattern-first Java playbook focused on problem recognition, invariants, complexity analysis, and reusable problem-solving techniques.
I’m prototyping an AI-assisted workflow that discovers contribution-friendly open-source repositories, scores suitable documentation issues, requests human approval, assists with implementation, and prepares pull requests.
