Director of Engineering, AI Platform

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🔥 0 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🔴 Lead

🤖 AI Engineer

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Medallion

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2020

⚕️ Healthcare Insurance

☁️ SaaS

🤖 Artificial Intelligence

🔥 Funding within the last year

💰 $43M Series C - Medallion on 2025-08

Healthcare Insurance • SaaS • Artificial Intelligence

Medallion is an AI-powered healthcare operations company that provides a SaaS platform to automate provider credentialing, payer enrollment, licensing, privileging, and ongoing monitoring. The platform uses machine learning and real-time automation to extract and standardize data, manage payer-specific and state rules, run automated follow-ups, and ensure compliance with NCQA and TJC standards—reducing costs and accelerating provider onboarding. Medallion serves payers, provider groups, health systems, RCM organizations, and digital health companies with a focus on lowering administrative burden and improving network readiness.

📋 Description

• 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. • 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. • 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. • 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. • 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.

🎯 Requirements

• 10+ years across engineering, ML, or data science, with experience leading a multi-team org through other managers. • You've run a mix of disciplines, including engineering, ML, data science, and data labeling or human-in-the-loop operations. • You've put applied ML and LLM systems into production, with the teams to back them, well beyond prototypes and research. • You understand LLMs, agents, retrieval, and structured extraction well enough to set direction, and you know what production reliability actually takes. • You're grounded in the data and infrastructure side: pipelines, orchestration, inference, and the eval and observability tooling that supports ML. • You weigh speed, cost, quality, and risk, and you take accuracy seriously where mistakes have real consequences.

🏖️ Benefits

• Health insurance • 401(k) plan • Flexible work hours • Professional development opportunities • Remote work options