Staff+ Software Engineer, Privacy

Responsibilities

• Design and implement privacy-preserving architectures for AI training and inference systems operating at very large scale, using techniques e.g. differential privacy, federated learning, and secure multi-party computation
• Partner with researchers to implement privacy-preserving training methods that protect user data while maintaining model quality
• Build foundational privacy infrastructure, including automated data discovery, classification, access controls, audit logging, and lifecycle management
• Translate regulatory requirements (e.g., GDPR, CCPA, HIPAA, the EU AI Act) into technical implementations and automated compliance controls
• Architect data governance systems for tracking data lineage, purpose limitation, and retention across distributed AI systems
• Lead privacy reviews and threat modeling for new models and features, identifying risks and designing scalable mitigations
• Partner with product and infrastructure teams to embed privacy controls into Claude's inference systems, user interfaces, and data pipelines
• Develop privacy engineering toolkits and frameworks that enable other engineers to build privacy-preserving features by default
• Design privacy-preserving analytics and measurement systems that surface useful insights without exposing individual user data
• Evaluate emerging privacy technologies from academia and industry, and contribute to open-source tooling and AI privacy standards

Languages