Software Engineer — backend, distributed systems & AI platforms
I build scalable services and AI-driven systems for production — from Spring Boot microservices on Kubernetes to agent-tool interfaces over the Model Context Protocol.
whoami
I'm a software engineer focused on backend development, distributed systems and cloud-native architectures. I work across Java, Python, Go, Docker, Kubernetes and AWS, building scalable services and AI-driven applications that run in production.
At Mendel, I build the AI platform behind intelligent expense management — a Spring Boot microservices ecosystem on AWS EKS. I own the WhatsApp conversational experience end to end: a Java orchestration layer and a Python AI agent for natural-language understanding and tool-based workflows.
I built and shipped our MCP (Model Context Protocol) server to production, exposing expense-audit and travel-approval tools to AI assistants like Claude — with an OAuth 2.0 authorization layer (Dynamic Client Registration, refresh tokens), delegated SSO and SSE streaming transport. Previously at Accenture I architected multi-agent AI systems with RAG pipelines, and I teach Microservices Architecture at ITBA.
focus[]
Intelligent automation and agent workflows that hold up under real production traffic.
Model Context Protocol servers that expose real tools to AI assistants, safely and with auth.
Services tuned for latency, throughput and cost — where the numbers actually matter.
Containerized workloads on Kubernetes, with the CI/CD and observability to keep them healthy.
Microservices that stay resilient as they scale, communicating over well-defined contracts.
git log --experience
Building the AI platform for intelligent expense management on Spring Boot microservices + AWS EKS. Owner of the WhatsApp conversational experience (Java BFF + Python AI agent) and of our production MCP server with OAuth 2.0, delegated SSO and SSE streaming.
Teaching and mentoring students in the design and implementation of microservice-based systems — lectures, hands-on labs and real-world exercises with Docker, Kubernetes, cloud-native tooling and modern communication patterns. Focused on deploying, scaling and observing distributed systems.
Built a multi-agent AI system on a customized n8n fork that routes user queries to specialized agents — designing agent workflows, integrating RAG pipelines and optimizing LLM response quality. Earlier, as an intern, worked across RAG/GraphRAG, prompt engineering and fine-tuning to improve enterprise-chatbot accuracy, cost and performance.
education --list
Six-year Computer Engineering degree (Bologna framework — B.Eng. + M.Eng. level), with a graduate focus on Software Architecture & Engineering.
work[]
Monitoring and operational automation for Docker environments — my ITBA final project.
Full-stack review app with a RESTful HATEOAS API — Spring + Hibernate backend, Angular front.
stack --list
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