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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and implementing privacy-preserving architectures and infrastructure for AI systems, with a strong focus on compliance with GDPR, CCPA, and other privacy regulations. Proficient in applying privacy engineering principles and leading privacy reviews and threat modeling efforts.
Highest-signal resume keywords
Privacy Engineering PrinciplesPython ProgrammingData Governance SystemsPrivacy Reviews and Threat ModelingDifferential Privacy Techniques
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Privacy By DesignData MinimizationPurpose LimitationSecure Multi-Party ComputationFederated LearningData Lifecycle ManagementRisk AssessmentsPrivacy Infrastructure DesignLarge-Scale Production SystemsTechnical Design Translation
Soft Skills
Written CommunicationVerbal Communication
Tools & Technologies
Privacy Engineering ToolkitsOpen-Source Privacy ToolingCloud InfrastructureDistributed Systems
Industry Keywords
GDPRCCPAHIPAAEU AI ActPrivacy PracticesAI Safety
Tech Stack
Tools & technologiesCloudDistributed SystemsPythonGo
About the role
Key responsibilities & impact- Design and implement privacy-preserving architectures for large-scale AI training and inference systems
- Apply differential privacy, federated learning, and secure multi-party computation techniques
- Partner with researchers to implement privacy-preserving training methods
- Build privacy infrastructure for data discovery, classification, access controls, audit logging, and lifecycle management
- Translate GDPR, CCPA, HIPAA, and EU AI Act 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
- Partner with product and infrastructure teams to embed privacy controls into Claude inference systems, user interfaces, and data pipelines
- Develop privacy engineering toolkits and frameworks
- Design privacy-preserving analytics and measurement systems
- Evaluate emerging privacy technologies and contribute to open-source tooling and AI privacy standards
- Advise on privacy practices as part of AI safety
Requirements
What you’ll need- Experience applying privacy engineering principles in production systems, including privacy by design, data minimization, and purpose limitation
- Proficiency in Python, Go, or similar languages
- 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
- 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
- Bachelor’s degree or an equivalent combination of education, training, and/or experience
- Relevant field of study demonstrated through coursework, training, or professional experience
- Visa sponsorship may be available
- Preferred: hands-on experience with privacy-enhancing technologies, including differential privacy, homomorphic encryption, secure enclaves, and 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 being 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 large-scale infrastructure
- Preferred: 3+ years leading large, complex projects as a technical lead
Benefits
Comp & perks- Optional equity donation matching
- Generous vacation
- Parental leave
- Flexible working hours
- Office space for collaboration
- Visa sponsorship support
- Competitive compensation
- Public benefit corporation mission focused on beneficial AI