Director, Quality Assurance

The Opportunity At our company, quality isn’t a hurdle to innovation—it’s the foundation that makes our data-driven insights trustworthy. You will not just be checking boxes; you will be defining the regulatory standards for the future of AI-driven drug discovery. As we transition into clinical-stage operations, we are looking for a Director of Quality Assurance to serve as a key architect of our quality culture. This is a "player-coach" role designed for a leader who can balance rigorous GXP compliance with the agility required in a data-driven, AI-forward company. You will stand up our clinical quality systems, manage global vendors, and partner with our Compute organization to define how the next generation of AI-driven medicine is validated and regulated. Based in South San Francisco, this position reports directly to the Chief Technology Operations Officer and offers an in person hybrid schedule of either three days per week or one full week per month. Responsibilities Clinical Quality & QMS Leadership Build the Foundation: Design and implement a robust, phase-appropriate Quality Management System (QMS), including Document Control, Deviations, CAPAs, and Change Control SOPs & Training: Author core SOPs and develop a streamlined training program that ensures compliance without creating unnecessary friction for the research and operations teams Phase-Appropriate Strategy: Provide expert guidance on maintaining compliance for early-phase clinical work while building a scalable bridge toward future commercialization Vendor Oversight: Lead the quality lifecycle for CROs/CMO/CDMOs. Perform audits for partners performing GLP, GCP, and GMP work to ensure they meet our internal and regulatory standards AI/ML & Computational Quality Partnership Algorithmic Integrity: Partner with the Compute and Data Science teams to establish a framework for the validation of AI/ML models used in patient selection, biomarker discovery, or clinical endpoint analysis Data Lineage & Governance: Collaborate with data engineers to ensure end-to-end traceability and data integrity—from raw biological data to final clinical insights Continuous Validation: Develop "phase-appropriate" monito ring for evolving algorithms to manage and document model drift in a regulatory-friendly manner Tech-Stack Qualification: Support the qualification of cloud-based compute environments to ensure they meet data storage and processing requirements for managing clinical data Strategic Operations & Risk Management Business Risk Oversight: Establish quality systems for research operations and business risk to protect the company’s intellectual and physical assets Stakeholder Partnership: Partner with diverse teams—from bench scientists to machine learning engineers—to demystify compliance and integrate quality into the daily workflow Sounding Board: Serve as a primary advisor to leadership, providing clear direction to ensure the company remains compliant with FDA, EMA, and global regulations...