Product Manager Intern (TikTok LIVE-AI & Ecosystem Governance) - 2027 Summer

The TikTok LIVE Governance team builds products, strategies, and governance systems that help maintain a safe, authentic, and sustainable live streaming ecosystem. We are evolving our governance products to responsibly apply AI—including large language models and agentic workflows—where they can improve risk discovery, decision support, governance quality, and operational efficiency. This internship is designed as a development opportunity for future Product Managers. Interns may be considered for full-time opportunities based on performance, eligibility, and business needs.

We are looking for talented individuals to join us for an internship. Our internship program offers students hands-on experience, industry exposure, and opportunities to apply their knowledge to real-world challenges while building a strong foundation for personal and professional growth. Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops alongside industry professionals. Candidates may apply to a maximum of two positions across Our Company and its affiliates globally. Applications will be considered in the order they are submitted. Applications are reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume, including your start and end dates.

Responsibilities: - Product Discovery and Execution: Identify ecosystem governance problems through user research, data analysis, and collaboration with operations and policy teams. Translate ambiguous problems into clear product requirements, roadmaps, and measurable outcomes. - AI-Enabled Governance Products: Explore where AI can meaningfully improve risk detection, decision support, user education, enforcement, and governance operations. Distinguish problems that are suitable for AI from those that require rules, conventional product solutions, or human judgment. - LLM Product Development and Evaluation: Work with Engineering, Machine Learning, Data Science, and Operations teams to prototype and evaluate LLM-enabled product capabilities. Define evaluation criteria and analyze failure modes such as hallucination, inconsistency, bias, false positives, and false negatives. - Agentic Workflow Design: Help design multi-step AI workflows involving task planning, tool use, retrieval, permissions, human review, escalation, and failure recovery. Ensure that agentic systems are observable, controllable, and appropriate for high-impact governance decisions. - Measurement and Iteration: Define success metrics across governance quality, user experience, operational efficiency, latency, and cost. Use offline evaluation, experiments, and production feedback to drive product iteration. - Cross-Functional Collaboration: Communicate product decisions and trade-offs clearly across global Product, Engineering, Algorithm, Data Science, Operations, Policy, and Legal stakeholders.