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Staff+ Software Engineer, Privacy
Anthropic is hiring for the job of Staff+ Software Engineer, Privacy, Friendly Travel-Required San Francisco, CA, WA New York City · Remote. This is a Privacy job in the governance, risk, and compliance field, with a posted range of $405,000. Review the full details below and apply directly with Anthropic.
About Anthropic
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.
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:
span $405,000 span span $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 a c-link--underline 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.
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 and 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 about a our policy for using AI in our application process.
Location and market context
This is a remote privacy job, so it draws from a national talent pool rather than a single metro. Remote governance and compliance jobs reward candidates who can show they work effectively across time zones and distributed legal, security, and product teams. Confirm any residency, travel, or occasional-onsite expectations directly with Anthropic.
About privacy jobs
Privacy jobs protect personal data across its lifecycle, from data mapping and DPIAs to individual-rights handling. AI systems are widening the scope of what privacy teams must review. Jobs like this one are typically evaluated against frameworks such as GDPR, CCPA and US state privacy laws, ISO/IEC 27701, and privacy-by-design practices.
How to position yourself for this privacy job
Strong candidates emphasize data mapping and inventories, privacy impact assessments, rights handling, and building privacy-by-design into products and AI systems. In your resume and outreach, tie your experience to how Anthropic would apply GDPR, CCPA and US state privacy laws, ISO/IEC 27701, and privacy-by-design practices, and lead with concrete outcomes rather than duties.
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