Staff+ Software Engineer, Privacy

United States Digital Space LLC; San Francisco (CA); Hybrid; USD 405,000 - 485,000; Full time

Job summary

United States Digital Space LLC is seeking a senior privacy engineer to establish the privacy function. You will architect privacy-preserving AI systems, lead data governance initiatives, and drive compliant designs across research, engineering, and product teams.

You will work at scale to protect user data, implement regulatory controls, and shape privacy strategies across the organization. This foundational role offers high autonomy and broad influence.

Qualifications

• Experience applying privacy engineering principles in production systems and data minimization.
• Proficiency in Python, Go, or similar languages, with work at scale.
• Experience designing privacy infrastructure for systems with large user bases.
• Experience with data governance, classification, or data lifecycle management.
• Understanding of GDPR, CCPA, and related regulations and translating them into technical designs.
• Experience conducting privacy reviews, threat modeling, or risk assessments.
• Strong written and verbal communication across multidisciplinary teams.

Responsibilities

• Design and implement privacy-preserving architectures for AI training and inference at very large scale using differential privacy, federated learning, and secure MPC.
• Partner with researchers to implement privacy-preserving training methods that protect user data and maintain model quality.
• Build foundational privacy infrastructure with automated data discovery, classification, access controls, audit logging, and lifecycle management.
• Translate regulatory requirements into technical implementations and automated compliance controls.
• Architect data governance systems for data lineage, purpose limitation, and retention across distributed AI systems.
• Lead privacy reviews and threat modeling for new models and features, identifying risks and scalable mitigations.
• Collaborate with product and infrastructure teams to embed privacy controls into AI systems, interfaces, and data pipelines.
• Develop privacy engineering toolkits and frameworks enabling engineers to build privacy-preserving features by default.
• Design privacy-preserving analytics and measurement systems that surface insights without exposing individual data.
• Evaluate emerging privacy technologies and contribute to open-source tooling and AI privacy standards.
• Advise on and advocate for privacy practices as a core part of AI safety.

Skills

Python

Go

Privacy engineering

Data governance

Threat modeling

Privacy by design

Production systems

Education

Bachelor's degree

Tools

Differential privacy

Homomorphic encryption

Secure enclaves

Secure multi-party computation

Job description

About the company

the company’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

the company 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 the company 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.

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.