Robinhood
Privacy Engineer
About this role
Robinhood seeks a Privacy Engineer to embed privacy protections across its financial technology platform. You'll conduct architecture reviews, design privacy-enhancing solutions, and leverage AI to automate privacy operations while ensuring compliance with global regulations.
What you'll do
- Conduct privacy architecture reviews to identify risks and recommend controls
- Partner with Engineering, Product, Legal, and Compliance to implement privacy-by-design
- Build and deploy AI agents to automate and scale privacy operations
- Guide selection and deployment of privacy-enhancing technologies
- Monitor regulatory developments and adjust practices for compliance
- Lead internal training to increase privacy awareness across technical teams
What they're looking for
- Privacy architecture and design
- Data privacy regulations (GLBA, GDPR, CCPA)
- Privacy-enhancing technologies and data anonymization
- AI and agentic systems development
- Security and cybersecurity fundamentals
- Cross-functional communication and stakeholder management
- Technical systems design and implementation
- Data governance and secure data lifecycle management
Benefits
- Performance-driven compensation with equity and 401(k) matching
- 100% paid health insurance for employees, 90% for dependents
- Flexible lifestyle wallet for wellness and learning
- Employer-paid life, disability, fertility, and mental health benefits
- Generous paid time off and parental leave
- Catered meals and exceptional office experience
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Robinhood
Robinhood builds financial products and platforms including brokerage, incentives, and identity verification services that serve millions of users. The company is hiring backend engineers to develop scalable fintech infrastructure, quality assurance engineers to test mobile and web applications, internal platform engineers to maintain Salesforce systems, and IT support specialists.
- Website
- robinhood.com
Likely interview questions
- Walk us through a recent privacy architecture review you led—what risks did you identify and how did you recommend addressing them?
- Describe your hands-on experience building or deploying AI agents; what operational or technical problems did they solve?