Designs and implements privacy-preserving architectures for AI systems, builds privacy infrastructure, and leads threat modeling to protect user data at scale. Requires deep privacy engineering expertise, production systems experience in Python/Go, and familiarity with regulations like GDPR/CCPA.
405k – 625k/yr
Hybrid15+ YOESecurity Engineering
About the role
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.
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.
Nice-to-Haves
15+ years (not including internships or co-ops) of experience in a Software Engineer role, building and operating large-scale developer infrastructure.
3+ years (not including internships or co-ops) of experience leading large scale complex projects or teams as a tech lead.
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Hybrid8+ YOESecurity Engineering
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