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AnthropicAnthropicSan Francisco, CA

Staff+ Software Engineer, Privacy

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.

Skills

PythonGoDifferential PrivacyFederated LearningSecure Multi-Party ComputationHomomorphic EncryptionSecure EnclavesThreat ModelingData GovernanceGDPRCCPA
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