Staff+ Software Engineer, Privacy

About Anthropic

Anthropics 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.

About the role

Anthropic is working on frontier AI systems that handle sensitive information at enormous scale. How we protect that data and how we build privacy into our systems rather than bolting it on afterward is central to our mission of building AI that is safe and beneficial.

This is a foundational role. As one of our first dedicated privacy engineers you will help establish the privacy engineering function at Anthropic and shape how privacy is designed into our AI systems from the ground up. Youll architect privacy-preserving systems lead the implementation of privacy-enhancing technologies across our infrastructure and provide technical leadership on privacy across engineering research and product teams.

Youll work at the intersection of privacy engineering AI safety and distributed systems solving problems that dont yet have established answers. This is a senior individual contributor role with high autonomy and broad influence.

Key responsibilities

• 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 Claudes 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

Minimum qualifications

• Experience applying privacy engineering principles in production systems including privacy by design data minimization and purpose limitation
• Proficiency in Python Go or similar languages with experience building and operating production systems at scale
• Experience designing and implementing privacy infrastructure for systems with a large user base
• Experience with data governance classification or data lifecycle management systems
• Understanding of privacy regulations such as GDPR and CCPA and the ability to translate legal requirements into technical designs
• Experience conducting privacy reviews threat modeling or risk assessments
• Written and verbal communication skills sufficient to drive alignment across engineering research legal and product teams

Preferred qualifications

• Hands-on experience with privacy-enhancing technologies (e.g. differential privacy homomorphic encryption secure enclaves secure multi-party computation)
• Experience building privacy infrastructure or controls for machine learning or AI systems
• Experience establishing a privacy engineering practice or being an early hire in a function
• Experience with distributed systems and cloud infrastructure at scale
• Experience serving as a technical lead on complex multi-quarter projects
• 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

Logistics

Minimum education: Bachelors 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 arent 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 youre interested in this work. We think AI systems like the ones were 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 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 youre ever unsure about a communication dont click any linksvisit for confirmed position openings.

How were 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. Were 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.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic including: GPT-3 Circuit-Based Interpretability Multimodal Neurons Scaling Laws AI & Compute Concrete Problems in AI Safety and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits optional equity donation matching generous vacation and parental leave flexible working hours and a lovely office space in which to collaborate with colleagues. Guidance on Candidates AI Usage:Learn aboutour policy for using AI in our application process.