Medallion - Director of Engineering, AI Platform
Requirements
• Manager of managers. 10+ years across engineering, ML, or data science, with experience leading a multi-team org through other managers. • Breadth across functions. You've run a mix of disciplines, including engineering, ML, data science, and data labeling or human-in-the-loop operations, rather than a single eng team. • Breadth across functions. • Shipped ML/AI at scale. You've put applied ML and LLM systems into production, with the teams to back them, well beyond prototypes and research. • Shipped ML/AI at scale. • Hands-on AI depth. You understand LLMs, agents, retrieval, and structured extraction well enough to set direction, and you know what production reliability actually takes. • Hands-on AI depth. • Data platform strength. You're grounded in the data and infrastructure side: pipelines, orchestration, inference, and the eval and observability tooling that supports ML. • Data platform strength. • Owns the outcome. You weigh speed, cost, quality, and risk, and you take accuracy seriously where mistakes have real consequences. • Owns the outcome.
Responsibilities
• Own the AI roadmap. Set direction across our AI surfaces: voice and computer-use agents that work payers and provider portals, email triage, and the models that extract and structure data from clinical and legal documents. The build-vs-buy and fine-tune-vs-prompt calls are yours. • Own the AI roadmap. • Push AI deeper. Take our systems from assisting people, to making decisions, to running whole service requests, and into licensing, enrollment, monitoring, and the customer-facing product. • Push AI deeper. • Make it production-grade. Build the evals, observability, and human-in-the-loop systems that let us ship models and agents we'll stand behind and back with guarantees. • Make it production-grade. • Lead the data platform. Own the pipelines, datasets, and tooling behind the models. Our real-world data is our biggest advantage, so make it fast to use and trustworthy to build on. • Lead the data platform. • Build the org. Hire and grow managers and senior engineers, set the structure, and hold the bar as we scale. Stay close enough to the work to earn their trust in a design review. • Build the org.
Benefits
• The healthcare back office is about to be reinvented, and we're the ones doing it. We started with licensing, credentialing, and enrollment, but the ambition is bigger: every workflow we automate earns the right to take on the next, until we run the back office end to end. It's the kind of problem applied AI is finally good enough for, and we're positioned to do it. 300+ organizations run on Medallion today, which gives us proprietary data, verifiable ground truth, and tight production feedback loops, plus the domain expertise and funding to go after it properly. • Getting there means applying ML and AI across more of the back office, a data platform that makes those systems reliable, and the team to build it all. • We prioritize candidate safety. Please be aware that official communication will only come from @medallion.co email addresses.
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