About

I’m Siobhan, a software engineer who works at the intersection of AI systems, data, and practical product engineering. I grew up in New Mexico, where I first got into programming when my IBMer grandfather encouraged me to study computer science.

My work today focuses on applied AI — retrieval architectures, LLM reasoning pipelines, model evaluation frameworks, and the infrastructure required to make intelligent systems reliable in production. I’m especially interested in how we can design tooling that makes AI measurable, testable, and genuinely useful for analytical and decision-making workflows.

I’m currently a founding engineer at Alkemi, working on end-to-end AI analytics and data tooling. Before that, I built developer-productivity systems at Trunk, large-scale ML data platforms at Meta’s Reality Labs, and enterprise data and ML systems across several startups.

Across all of these roles, the common thread has been turning ambiguous technical problems into clear, durable systems that people can trust.

I enjoy collaborating with thoughtful teams, contributing to ambitious products, and exploring new ways AI can augment technical work. If you’re building something interesting and want to talk, I’d love to connect.