1 month ago
Base Salary
$405k - $485k/yr
Responsibilities
- Design and implement privacy-preserving architectures for large-scale AI training and inference using 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 privacy infrastructure for data discovery, classification, access controls, audit logging, and lifecycle management.
- Translate regulatory requirements including GDPR, CCPA, HIPAA, and the EU AI Act 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 and design scalable mitigations.
- Embed privacy controls into Claude’s inference systems, user interfaces, and data pipelines.
- Develop privacy engineering toolkits and frameworks that enable privacy-preserving features by default.
- Design privacy-preserving analytics and measurement systems that provide insights without exposing individual user data.
- Evaluate emerging privacy technologies and contribute to open-source tooling and AI privacy standards.
- Advise engineering, research, product, and infrastructure teams on privacy practices as part of AI safety.
Requirements
- Experience applying privacy engineering principles in production, including privacy by design, data minimization, and purpose limitation.
- Proficiency in Python, Go, or similar languages and experience building and operating production systems at scale.
- Experience designing 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 ability to translate legal requirements into technical designs.
- Experience conducting privacy reviews, threat modeling, or risk assessments.
- Communication skills sufficient to build alignment across engineering, research, legal, and product teams.
- Preferred: hands-on experience with differential privacy, homomorphic encryption, secure enclaves, or secure multi-party computation.
- Preferred: experience building privacy infrastructure or controls for machine learning or AI systems.
- Preferred: experience establishing a privacy engineering practice or serving as an early hire in a function.
- Preferred: experience with distributed systems and cloud infrastructure at scale.
- Preferred: experience serving as a technical lead on complex, multi-quarter projects.
- Preferred: contributions to open-source privacy tooling, privacy research, or industry standards.
- Preferred: 12+ years of software engineering experience, including building and operating large-scale infrastructure.
- Preferred: 3+ years leading large, complex projects as a technical lead.
- A bachelor’s degree or equivalent combination of education, training, and/or experience in a relevant field is required.
Benefits
- Annual compensation range of $405,000-$485,000 USD.
- Hybrid policy requiring staff to work from an office at least 25% of the time.
- Visa sponsorship may be available, with immigration lawyer support.
- Competitive benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office collaboration space.
About Anthropic
Anthropic builds large language models and the Claude AI assistant for developers and enterprises, offered via API access and enterprise plans. Founded in 2021 and headquartered in San Francisco, it distributes Claude through its own platform and via partners such as Amazon Bedrock and Google Cloud’s Vertex AI. Its work emphasizes model reliability, interpretability, and practical tooling for tasks like coding assistance, analysis, and customer support automation.