Staff+ Software Engineer, Privacy

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.

• 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

• 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

Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below.

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

• 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

$405,000—$485,000 USD

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.