Staff+ Software Engineer, Privacy
San Francisco, CA | New York City, NY | Seattle, WA
Posted 16d ago
About the job
Anthropic is seeking a seasoned Privacy Engineer to join its growing team and help scale privacy infrastructure within the AI landscape. This individual contributor role involves providing technical and cultural leadership, architecting privacy-preserving systems, and driving the implementation of cutting-edge privacy technologies across AI infrastructure. The position operates at the intersection of privacy engineering, AI safety, and distributed systems to address novel challenges in protecting user data at scale.
Responsibilities
- Design and implement privacy-preserving architectures for AI training and inference systems using differential privacy, federated learning, and secure multi-party computation.
- Partner with AI researchers to implement privacy-preserving training methodologies that maintain model quality while protecting user data.
- Build foundational privacy infrastructure including automated data discovery, classification, access controls, audit logging, and lifecycle management systems.
- Translate complex regulatory requirements (GDPR, CCPA, HIPAA, EU AI Act) into actionable technical implementations and automated compliance controls.
- Architect comprehensive data governance platforms for tracking data lineage, purpose limitation, and retention across distributed AI systems.
- Lead technical privacy reviews and threat modeling for new AI models and features, identifying risks and architecting scalable mitigations.
- Collaborate with product and infrastructure teams to embed privacy controls into AI systems, user interfaces, and data pipelines.
- Develop privacy engineering toolkits and frameworks to enable engineers to build privacy-preserving features by default.
- Design and implement privacy-preserving analytics and measurement systems that provide insights while protecting individual user privacy.
- Research and evaluate emerging privacy technologies, contributing to open-source tools and AI privacy standards.
- Act as a consultant and advocate for privacy best practices as central to the mission of AI safety.
Requirements
- Deep expertise in privacy engineering principles: privacy by design, data minimization, purpose limitation.
- Strong programming skills in Python, Go, or similar languages with experience building production systems at scale.
- Experience with privacy-enhancing technologies (differential privacy, homomorphic encryption, secure enclaves).
- Proven track record of designing and implementing privacy infrastructure serving millions of users.
- Expertise in data governance, classification, and lifecycle management systems.
- Strong understanding of privacy regulations (GDPR, CCPA) and ability to translate legal requirements into technical solutions.
- Experience conducting privacy reviews, threat modeling, and risk assessments.
- BS/MS in Computer Science, Engineering, or equivalent practical experience.