Team Introduction:
The TikTok LIVE Governance team builds products, strategies, and governance systems that help maintain a safe, authentic, and sustainable livestreaming 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.
Minimum Qualifications
- Currently pursuing an Undergraduate degree, or demonstrating equivalent experience through projects, research, internships, or entrepreneurial work.
- Able to commit to working for 12 weeks with 4 days onsite during Spring 2027.
- Has work-authorization, and meet the onsite requirements applicable to the hiring location.
- Strong product thinking and structured problem-solving skills, with the ability to translate complex or ambiguous problems into actionable product plans.
- Foundational understanding of AI, large language models, and agentic systems, including their capabilities, limitations, and appropriate product applications.
- Experience experimenting with AI products or tools, with the ability to critically evaluate output quality rather than treating model responses as inherently correct.
- Strong analytical and communication skills, with the ability to work effectively across technical and non-technical teams, interest in livestreaming, creator ecosystems, content governance, or trust and safety.
Preferred Qualifications
- Currently pursuing a Master's degree, or demonstrating equivalent experience through projects, research, internships, or entrepreneurial work.
- Able to commit to continuing to work onsite during Summer 2027.
- Experience building or evaluating an AI/LLM-enabled prototype through coursework, research, hackathons, internships, or personal projects.
- Familiarity with concepts such as prompting, retrieval-augmented generation, model evaluation, tool calling, agent workflows, human-in-the-loop systems, or AI safety.
- Basic proficiency with SQL, Python, APIs, prototyping tools, or experimentation methods.
- Experience in product management, online platforms, creator products, content governance, responsible AI, or trust and safety.
- Demonstrated ability to learn quickly, investigate failure modes, and iterate based on evidence and user feedback.
