Anthropic

Staff+ Software Engineer, Privacy

Anthropic

New York•Hybrid•12+ Yrs•1 day ago

Hybrid

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems.

Design and implement privacy-preserving architectures for AI training and inference systems operating at very large scale, using techniques such as 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
Advise on and advocate for privacy practices as a core part of how we approach AI safety

Proficiency in Python, Go, or similar languages, with experience building and operating production systems at scale
Understanding of privacy regulations such as GDPR and CCPA, and the ability to translate legal requirements into technical designs
Written and verbal communication skills sufficient to drive alignment across engineering, research, legal, and product teams
Contributions to open-source privacy tooling, privacy research, or industry standards
12+ years of experience in a software engineering role, including building and operating large-scale infrastructure
3+ years of experience leading large, complex projects as a technical lead
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Hands-on experience with privacy-enhancing technologies (e.g., differential privacy, homomorphic encryption, secure enclaves, secure multi-party computation)

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