Engineering Director – Surgical Data Annotation & Programs

Provide strategic and operational leadership for a portfolio of high throughput, clinically defensible, audit ready surgical video annotation programs. Own scale, standardization, automation leverage, quality systems, and client trust across multiple programs—ensuring predictable delivery, regulatory readiness, and measurable ROI on human in the loop operations.

Responsibilities

Own end to end delivery for multiple concurrent surgical video annotation programs; Set and enforce standard operating models from intake → de identification → annotation → QA/IRR → adjudication → dataset release + evidence packs; Define and institutionalize annotation operating standards; Partner with senior clinical SMEs to define and approve procedure level ontologies; Set the automation vision and roadmap for surgical video labeling; Design and govern enterprise grade quality systems; Own disagreement governance across programs; Ensure all annotation programs comply with de identification standards, data access controls, logging, retention, and audit requirements; Act as senior escalation and trusted advisor for clients; Build and lead a multi layered delivery organization; Own portfolio level metrics

Requirements

12–15+ years of hands-on experience in data operations, annotation programs, QA-led delivery, or clinical data management; 5+ years leading managers or owning multi-program portfolios; Deep, hands-on expertise with video annotation programs, including temporal segmentation, event labeling, and annotation tool workflows at scale; Proven track record designing and running enterprise-grade quality systems with IRR accountability; Strong executive program management skills: capacity planning, financial control, risk management, and stakeholder leadership; Demonstrated ability to operationalize clinical guidelines into enforceable, tool-based workflows; Experience working in regulated or high-trust environments (healthcare, life sciences, sensitive data handling)

Nice to have

Direct experience with surgical video data (endoscopy, robotics, OR cameras); Prior ownership of automation or ML assisted labeling programs at scale; Experience leading dataset versioning, reproducibility, and audit ready release processes; Exposure to enterprise security, privacy, and compliance frameworks; Background in building delivery organizations from early scale to maturity