The posting
The TikTok Privacy and Security (PnS) R&D team creates privacy solutions that are intuitive for users, auditable for regulators, and sustainable for the company, making TikTok a platform where people can safely discover, create, and connect.
We build user-facing privacy features, including privacy settings, consent management, data access and export, and age-appropriate experiences. We protect personal data across its full lifecycle, from collection and transfer through access, storage, retention, and deletion. We develop the platforms, technical controls, and governance tools behind privacy protection and regulatory compliance in global markets, and we bring privacy-enhancing technologies and research into production at scale. We tackle challenges unique to operating a platform at global scale: translating rapidly evolving laws and policies into reliable technical controls, providing transparency and auditability across highly complex data systems, supporting different regulatory requirements across regions, and making privacy protection work at the quality and speed production systems demand.
You will work across product privacy, data lifecycle management, data protection and residency, privacy engineering platforms, AI governance, and privacy-preserving technologies, using techniques including automated compliance enforcement, data lineage and taxonomy, differential privacy, trusted execution environments, AI fairness, and privacy protection for generative AI. The systems you build will protect hundreds of millions of people, and the privacy decisions you make will reach every one of them.
The TikTok Privacy and Security Product DSR team builds the platform behind data subject requests: the rights users exercise to access, delete, correct, or export their data. The team turns those rights into systems that run accurately, on time, and at global scale, across the products and data stores where that data actually lives. In this role, you will design and build core DSR systems, apply judgment where business goals and compliance meet, and take that work end to end with partner teams.
Responsibilities As a Sr. Software Engineer on the TikTok Privacy and Security Product DSR team, you will: - Design, build, and evolve backend systems that improve privacy across TikTok, and help turn repeated requirements into shared platform capabilities. - Make sound business and compliance judgments in the systems you own, and carry the work end to end: problem framing, technical design, delivery, launch, and adoption. - Partner across product, legal, policy, data, and engineering teams. Align on requirements and tradeoffs, and land privacy capabilities in the products and data systems that depend on them. - Work with data and its lifecycle. Implement how data is collected, stored, used, shared, retained, and deleted, and connect those controls to how products operate. - Use data analysis and data processing to measure privacy coverage, risk, and business impact, and extend privacy capabilities into new scenarios and product lines. - Build and operate high-scale backend services, and take part in privacy incident response, including scope, root cause, and remediation.
Minimum Qualification(s) - Bachelor's or Master's degree in Computer Science or a related field, or equivalent practical experience. - Experience building backend services for large-scale, consumer-facing products. - A solid grasp of data, its lifecycle, and how data systems support the business. - Ability to make sound judgments on business and compliance tradeoffs, and to plan and deliver work end to end. - Experience working with partner teams across organizations, and communicating clearly enough to land a shared technical decision. - Proficiency in at least one of Java, Go, C++, or Python. - Strong fundamentals in data structures, algorithms, and backend system design.
Preferred Qualification(s) - Experience on a large platform, such as infrastructure, ads, recommendation, or an open platform. - Experience contributing to longer-term platform planning, or turning fragmented capabilities into a shared service. - Hands-on experience with data analysis and data processing, and with using those skills to support new business use cases. - Experience designing or implementing privacy, data governance, or trust and safety features. - Experience operating systems at very large consumer scale.
