Staff+ Software Engineer, Privacy

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. You'll sit within our Data Infrastructure team, architecting privacy-preserving systems, leading the implementation of privacy-enhancing technologies across our infrastructure, and providing technical leadership on privacy across engineering, research, and product teams.

You'll work at the intersection of privacy engineering, AI safety, and distributed systems, solving problems that don't 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 e.g. 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

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 build 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

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.

Annual Salary:

$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.

How we're different

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 about our policy for using AI in our application process.