Curious, technically rigorous,
leads with warmth.

I'm Italo — a mathematician-turned-engineer who builds AI systems that actually ship. My path has taken me through five of the world's largest tech companies, but the thread that connects it all is a deep curiosity about how things work and a drive to make complex systems useful.

At Microsoft, I lead AI product development for Fabric Real-Time Intelligence, where I've built three AI products from zero to one: an anomaly detector for streaming data, an LLM-powered operations agent with reward modeling, and an automated operational discovery system. Before that, I spent time at Google, Pinterest, Netflix, and Meta — each stop sharpening a different facet of the craft.

My Ph.D. in Mathematics from Auburn University gave me something that's hard to train on the job: comfort with deep abstraction and a rigorous approach to uncertainty. I think about AI systems the way a mathematician thinks about proofs — what are the assumptions, where are the failure modes, and how do we know this actually works?

How I work

I believe the best AI systems come from people who are both technically deep and genuinely collaborative. I write code, design evaluations, build prototypes, and ship products — but I also care about communicating clearly, mentoring with patience, and creating the kind of psychological safety where good ideas can surface from anywhere.

I sign my emails lowercase. I ask questions because I want to understand, not to interrogate. I believe warmth and rigor aren't in tension — they're complementary.

Tools & environment

Python is my primary language, with deep experience in PyTorch, LLM frameworks, and ML infrastructure. I work in nvim with oh-my-zsh, and I'm most productive when I can move fluidly between prototyping and production code. I care about developer experience because friction in tools translates to friction in thinking.