https://www.lucavallin.com/blog/tags/ai Platform Engineer at Xebia, focused on AI platform engineering - the infrastructure behind reliable, observable, scalable AI and cloud-native workloads. I work primarily in Go and Google Cloud, with deep experience in Kubernetes, containers, and end-to-end observability - and a strong interest in networking and lower-level systems work in Rust. My current focus is the platform layer beneath AI: inference serving infrastructure on Kubernetes, AI gateway and MCP connectivity, agentic workload orchestration, and end-to-end observability for GenAI systems. My broader experience is full-stack: strong on backend, with solid frontend and mobile knowledge. I contribute to open source, write on my blog, and pick up the occasional talk, training, or meetup when something interesting comes up. I'm a Google Developer Expert (GDE) and a CNCF Ambassador. For a deeper dive, see my blog. If you're new to open source, check out Verto.sh. For mentorship, I'm on Mentorcruise. Outside of work, activities like photography, motorcycling, playing a handpan and cleaning litterboxes keep me occupied 🐈. en-us Luca Cavallin Luca Cavallin Tue, 02 Jun 2026 00:00:00 GMT https://www.lucavallin.com/blog/ai-engineering-for-developers https://www.lucavallin.com/blog/ai-engineering-for-developers A tour through AI engineering for developers who already know how to ship software. Fourteen chapters, no LinkedIn voice, no slow warm-up. We will go from 'what is a foundation model' to 'how do you run agents in production on Google Cloud' without skipping the parts that matter. Tue, 02 Jun 2026 00:00:00 GMT Luca Cavallin ai https://www.lucavallin.com/blog/notes-i-took-while-reading-applied-machine-learning-and-ai-for-engineers-and-introducing-mlops https://www.lucavallin.com/blog/notes-i-took-while-reading-applied-machine-learning-and-ai-for-engineers-and-introducing-mlops I recently read the books "Applied Machine Learning and AI for Engineers" and "Introducing MLOps", and I took some notes to make a quick summary of all the stuff packed into these books. In this post, I'm sharing my takeaways, from the basics of supervised and unsupervised learning to the more complex areas like deep learning and natural language processing, as well as the core ideas behind MLOps. Thu, 18 Jul 2024 00:00:00 GMT Luca Cavallin ai