Anthropic· Software Engineering - Infrastructure· San Francisco, CA | New York City, NY | Seattle, WA
Staff+ Software Engineer, Privacy
Classified Tasks (17)
Automate 0%Augment 71%Human-Only 29%
Augment (12)
AI assists, human decides
Architect innovative privacy-preserving systems for AI.
technical
Drive implementation of cutting-edge privacy technologies across AI infrastructure.
operational
Design and implement privacy-preserving architectures for AI training and inference systems using differential privacy, federated learning, and secure multi-party computation.
technical
Partner with AI researchers to implement privacy-preserving training methodologies that maintain model quality while protecting user data.
technical
Build foundational privacy infrastructure including automated data discovery, classification, access controls, audit logging, and lifecycle management systems.
technical
Translate complex regulatory requirements into actionable technical implementations and automated compliance controls.
analytical
Architect comprehensive data governance platforms for tracking data lineage, purpose limitation, and retention across distributed AI systems.
technical
Collaborate with product and infrastructure teams to embed privacy controls into inference systems, user interfaces, and data pipelines.
communication
Develop privacy engineering toolkits and frameworks to enable engineers to build privacy-preserving features by default.
technical
Design and implement privacy-preserving analytics and measurement systems that protect individual user privacy while providing insights.
technical
Research and evaluate emerging privacy technologies and contribute to open-source tools and AI privacy standards.
analytical
Integrate privacy practices across AI safety and distributed systems to protect user data at scale.
operational
Human-Only (5)
Requires human judgment
Provide technical and cultural leadership for the privacy engineering team.
leadership
Solve novel challenges in protecting user data at scale.
analytical
Lead technical privacy reviews and threat modeling for new AI models and features, identify risks, and architect scalable mitigations.
leadership
Act as a consultant and advocate for privacy best practices across the organization.
communication
Define and shape privacy architecture and standards for AI systems from inception.
leadership
Job description
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We're seeking an exceptional seasoned Privacy Engineer to join our growing privacy engineering team and help scale our privacy infrastructure as we navigate the transformative AI landscape. As one of our first dedicated privacy engineers, you'll have an outsized impact in shaping how Anthropic builds world-class privacy into our AI systems from the ground up. This is a seasoned individual contributor role where you'll provide technical and cultural leadership, architect innovative privacy-preserving systems, and drive implementation of cutting-edge privacy technologies across our AI infrastructure. You'll work at the intersection of privacy engineering, AI safety, and distributed systems to solve novel challenges in protecting user data at scale. Responsibilities: Design and implement privacy-preserving architectures for AI training and inference systems handling billions of conversations, leveraging 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 Claude's inference systems, user interfaces, and data pipelines Develop privacy engineering toolkits and frameworks that enable all 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 from academia and industry, contributing to open-source tools and AI privacy standards Act as consultant and advocate for privacy best practices as central to our mission of AI safety You might be a good fit if you have: 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 Strong Candidates May Also Have:</