Content Governance Engineer (Java / Go)

Responsibilities:

• Design, develop, and iterate on content governance platforms, anti-abuse tooling, and content operations tools.
• Drive the integration of recommendation systems with content governance capabilities, building efficient, stable, and scalable governance pipelines.
• Collaborate with governance and product teams to deliver content review, risk detection, and policy enforcement system capabilities.
• Design and implement content takedown rules, conducting ongoing adversarial defense, effectiveness evaluation, and rule optimization.
• Build and optimize content governance rule engines, improving rule configuration, gradual rollout, retrospective analysis, and operations management efficiency.
• Provide systematic governance solutions for spam, traffic diversion, low-quality content, black/gray-market activity, fraud, and low-quality shilling.

Requirements:

• Proficient in Java or Go, with solid engineering design and system development skills.
• Familiar with distributed systems, microservice architecture, message queues, caching, and relational databases.
• Understanding of content governance workflows, including content review, risk detection, policy enforcement, and effectiveness evaluation.
• Familiar with rule engines or policy platforms, able to abstract governance requirements into configurable, extensible system capabilities.
• Understanding of common content platform ecosystem issues and governance approaches, with risk awareness and adversarial thinking.
• Strong cross-team communication skills, able to collaborate effectively with product, operations, algorithm, and business teams.

Preferred qualifications:

• Experience with recommendation systems, recommendation engineering, or content distribution systems.
• Experience in content safety, anti-fraud, risk control, or black/gray-market adversarial defense.
• Experience building large-scale content governance platforms, rule engines, or policy operations platforms.
• Familiarity with applying machine learning models to content review, risk detection, or recommendation governance.