AI Safety Platform Engineer - Data Governance

TikTok USDS Joint Venture; San Jose (CA); On-site; USD 187,000 - 360,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k) with company match

Parental leave

Short-term and long-term disability

Job summary

TikTok USDS Joint Venture LLC is building the AI safety platform and governance layer that ensures privacy, security and policy compliance for data used in models. This role focuses on engineering scalable control planes and automated safety workflows across large-scale data environments.

You will join a mission-driven team creating privacy-as-code engines and governance integrations that enforce model safety, data lineage, and RTBF across the ML training and inference lifecycle.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related technical field.
• 2+ years Backend Engineering experience in Go, Java, or C++ (Go preferred).
• Experience with high-volume data ecosystems (Hive, Spark, Kafka, Flink, Kubernetes).
• Deep understanding of Database Design, SQL, and NoSQL internals.

Responsibilities

• Design and scale AI safety platforms that are auditable and compliant with USDS standards.
• Architect low-latency interception systems to enforce safety guardrails in real time.
• Build distributed systems for automated data lineage and RTBF workflows across ML training/inference lifecycles.
• Develop backend services for seamless integration of safety models into TikTok infrastructure.
• Create centralized observability dashboards and risk telemetry for real-time safety visibility.

Skills

Go

Java

C++

Big Data

Hive

Spark

Kafka

Flink

Kubernetes

SQL

NoSQL

Education

Bachelor’s or Master’s degree

Tools

Hive

Spark

Kafka

Flink

Kubernetes

Job description

TikTok USDS Joint Venture LLC is building the AI safety platform and governance layer that ensures privacy, security and policy compliance for data used in models. This role focuses on engineering scalable control planes and automated safety workflows across large-scale data environments.

You will join a mission-driven team creating privacy-as-code engines and governance integrations that enforce model safety, data lineage, and RTBF across the ML training and inference lifecycle.