Ben Drolet
AI infrastructure engineering for healthcare
I help healthcare companies build the LLM platforms and internal AI tooling their engineers need to ship production AI products safely.
Get in touch →The Problem
Most healthcare organizations trying to build with AI hit the same wall: the product vision is clear, but the infrastructure underneath isn't.
Taking an AI pilot to production in healthcare is harder than it looks. LLM deployments break without the right abstractions. Engineers rebuild the same tooling on every project. HIPAA and regulatory constraints add requirements that generic AI architectures don't handle.
Getting the infrastructure right early determines whether your AI program ships or stalls.
What I Do
LLM Platform Engineering
Design and build the infrastructure for LLM-powered applications — model routing, prompt management, evaluation pipelines, LLM observability, hallucination detection, and deployment systems that survive model upgrades.
Internal AI Developer Platforms
Build the tooling and abstractions that let product engineers use AI without becoming AI infra engineers — shared components, standardized access patterns, AI guardrails, and the HIPAA-compliance layer that healthcare requires.
About
16 years as a backend software engineer. For the past 4 years, focused on healthcare — behavioral health, digital health, and health tech — where the infrastructure problems are harder and the cost of getting it wrong is higher. Recently focused on the infrastructure side of AI — building the LLM platforms, evaluation pipelines, and internal developer tooling that production AI applications run on.
I work with healthcare engineering teams that have serious AI ambitions and need the infrastructure layer built right.
Based in San Francisco.
Contact
If you're building AI infrastructure in healthcare, I'd like to hear what you're working on.
[email protected]