About the role
Company Overview: We are building Protege to solve the biggest unmet need in AI — getting access to the right training data. The process today is time intensive, incredibly expensive, and often ends in failure. The Protege platform facilitates the secure, efficient, and privacy-centric exchange of AI training data. Solving AI’s data problem is a generational opportunity. We’re backed by world-class investors and already powering partnerships with some of the most ambitious teams in AI. The company that succeeds will be one of the largest in AI — and in tech. We’re a lean, fast-moving, high-trust team of builders who are obsessed with velocity and impact. Our culture is built for people who thrive on ambiguity, own outcomes, and want to shape the future of data and AI. Role Overview: We’re looking for a Partnerships Operations Lead (Healthcare) to operationalize and scale the data partner ecosystem that powers Protege’s healthcare AI products. You will own execution — ensuring each healthcare partner is successfully onboarded, technically integrated, commercially aligned, and consistently delivering on customer engagements. You will sit at the intersection of partnerships, science, product, and customer delivery — translating signed agreements into reliable, high-quality data supply. This role requires deep understanding of healthcare data operations, strong cross-functional coordination, and the ability to manage complexity across multiple concurrent deals. Key
Responsibilities: Operationalize Healthcare Data Partnerships Lead onboarding of new healthcare data partners, establishing repeatable operational playbooks Coordinate secure data access, querying workflows, and transfer mechanisms Partner with Product and Engineering to align on ingestion, normalization, and technical setup Ensure privacy, compliance, and governance
requirements are properly implemented in collaboration with Legal and Compliance Develop structured processes to scale partner onboarding efficiently Evaluate Data Readiness & Quality Conduct structured evaluations of partner datasets across EHR, imaging, claims, genomics, device, or real-world data Partner with DataLab to assess data completeness, quality, modality coverage, and fitness for AI training use cases Collaborate with scientific teams to support feasibility assessments for customer projects Identify data gaps, operational risks, and areas requiring remediation Establish partner performance scorecards tracking responsiveness, reliability, and data quality Execute on Customer-Specific Data Engagements Align partners on project