SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Anthropic is seeking a Staff Software Engineer for Privacy to establish and lead the privacy engineering function at the company. This is a foundational role for one of the first dedicated privacy engineers, sitting within the Data Infrastructure team.
You will architect privacy-preserving systems for AI training and inference at massive scale, implementing techniques like differential privacy, federated learning, and secure multi-party computation. Key responsibilities include designing privacy-preserving architectures for Claude's systems, building foundational privacy infrastructure (data discovery, classification, access controls, audit logging, lifecycle management), and translating regulatory requirements (GDPR, CCPA, HIPAA, EU AI Act) into technical implementations.
You'll lead privacy reviews and threat modeling for new models and features, develop privacy engineering toolkits that enable other engineers to build privacy-preserving features by default, and design privacy-preserving analytics systems. You'll partner with researchers, product teams, and infrastructure teams to embed privacy controls across the organization, and advise on privacy practices as a core part of AI safety.
This is a senior individual contributor role with high autonomy and broad influence across engineering, research, and product teams. You'll work at the intersection of privacy engineering, AI safety, and distributed systems, solving novel problems without established answers.
Required: Production experience with privacy engineering principles, proficiency in Python/Go or similar languages, experience designing privacy infrastructure for large user bases, data governance/lifecycle management experience, understanding of privacy regulations, privacy review/threat modeling experience, and strong cross-functional communication skills.
Preferred: Hands-on experience with differential privacy, homomorphic encryption, secure enclaves, or secure multi-party computation; privacy infrastructure for ML/AI systems; experience establishing privacy engineering practices; distributed systems and cloud infrastructure expertise; technical leadership on complex multi-quarter projects; open-source privacy contributions; 12+ years software engineering experience including large-scale infrastructure; 3+ years leading complex projects as technical lead.
