Staff+ Software Engineer, Privacy

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 such as GDPR, CCPA, HIPAA, and 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 inference systems, user interfaces, and data pipelines.
• Develop privacy engineering toolkits and frameworks that enable engineers to build privacy-preserving features by default.
• Design privacy-preserving analytics and measurement systems that provide 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.
• Advocate for privacy practices as a core part of AI safety.

Requirements

• 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, with 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.
• 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.
• Bachelor’s degree or an equivalent combination of education, training, and experience in a relevant field.

Nice-to-haves

• Hands-on experience with privacy-enhancing technologies such as differential privacy, homomorphic encryption, secure enclaves, and 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.

Compensation and Benefits

• Annual salary: $405,000–$485,000 USD.
• Hybrid policy: Staff are expected to work from an office at least 25% of the time; some roles may require more office time.
• Visa sponsorship is available for eligible roles and candidates.