Software Engineer - USDS

About the Team

You will join the TikTok USDS Data Governance Team, the architects of the foundational infrastructure that manages the entire data lifecycle. Our mission is to ensure the integrity, security, and compliance of our data assets through robust lifecycle management, automated frameworks, and advanced content assurance standards.



Our team operates at the high-stakes intersection of Data Infrastructure, Privacy Engineering, and AI Governance. We are building the "operating system" for data compliance, replacing manual policies with scalable, automated code that enforces security and privacy standards across one of the world's largest data ecosystems.



About the Role

As a Software Engineer on the Data Governance team, you will build the "digital nervous system" protecting US user data. You will move beyond traditional compliance to build Governance as Code—creating self-serve platforms, automated lineage engines, and intelligent assurance systems.



You will be responsible for turning complex legal, security, and content requirements into scalable technical realities. Your systems must handle the unique challenge of managing petabytes of data across heterogeneous environments (Offline, Real-time, Data Lake) while maintaining high reliability and engineering velocity.



Responsibilities:

Data Lifecycle Management: Design and scale systems for data inventory, lineage, and residual scanning to proactively remediate privacy risks across distributed storage.



AI & Recommendation Governance: Build metadata frameworks and control planes for Machine Learning pipelines, ensuring recommendation algorithms and training data adhere to safety and purpose-limitation protocols.



LLM Assurance & Safety: Develop technical frameworks to evaluate and mitigate risks in Large Language Model (LLM) outputs, focusing on safety filters, bias detection, and accuracy.



Compliance Engineering: Architect high-throughput engines to automate regulatory adherence and build centralized platforms that provide real-time observability into data security.



High-Scale Systems: Optimize distributed systems to handle the unique latency and reliability requirements of real-time recommendation environments.