Staff+ Software Engineer, Privacy

Anthropic•Seattle, WA

1d•Hybrid

About The Position

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. 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.

Requirements

10+ years of professional software engineering experience (not including internships and co-ops)
5+ years of experience focused on privacy, security, or data protection
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

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