Staff+ Software Engineer, Privacy

Anthropic; United States; Hybrid; USD 405,000 - 485,000; Full time

Job summary

Anthropic is seeking a senior privacy engineer to help establish the privacy engineering function within the Data Infrastructure team. You will architect privacy-preserving systems across AI training and inference, lead implementation of privacy-enhancing technologies, and guide cross‑functional teams in privacy across engineering, research, and product domains.

You'll work at the intersection of privacy engineering, AI safety, and distributed systems in a senior IC role with high autonomy and

Qualifications

• Privacy engineering principles in production systems (privacy by design, data minimization, purpose limitation).
• Proficiency in Python, Go, or similar languages for production systems.
• Experience designing privacy infrastructure for systems with a large user base.
• Experience with data governance, classification, or data lifecycle management.
• Understanding of GDPR, CCPA, HIPAA, and translating regulatory requirements into designs.
• Experience conducting privacy reviews, threat modeling, or risk assessments.
• Strong written and verbal communication across engineering, research, legal, and product teams.

Responsibilities

• Design and implement privacy-preserving architectures for AI training and inference systems at large scale.
• Partner with researchers to implement privacy-preserving training methods protecting user data while maintaining model quality.
• Build foundational privacy infrastructure, including data discovery, access controls, audit logging, and lifecycle management.
• Translate regulatory requirements into technical implementations and automated compliance controls.
• Lead privacy reviews and threat modeling for new models and features; design scalable mitigations.
• Partner with product and infrastructure teams to embed privacy controls into systems and data pipelines.
• Develop privacy engineering toolkits and frameworks for engineers to build privacy-preserving features by default.

Skills

Privacy engineering principles

Python/Go programming

Production systems at scale

Data governance

GDPR/CCPA knowledge

Threat modeling

Communication skills

Education

Bachelor's degree or equivalent

Tools

Differential privacy

Federated learning

Secure multi-party computation

Job description

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

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.

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.

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.

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.