Responsibilities

About the Team The TikTok Eng - PGC - Creator Strategy team builds technology that helps TikTok identify, incentivize, and grow high-quality professionally generated content while enabling creators to build sustainable careers on the platform. We develop the strategy and engineering infrastructure that turns creator and platform goals into scalable monetization programs, incentive mechanisms, product experiences, and governance solutions. One of the team's core products is the Creator Rewards Program, a key pillar of TikTok's creator monetization ecosystem. The team supports the end-to-end creator journey—from eligibility and enrollment to reward calculation, earnings transparency, content and account governance, and payout—across multiple global markets. We work at the intersection of large-scale backend engineering, creator strategy, incentive design, monetization, and trust and safety. You will collaborate closely with Product, Data Science, Research, Design, Operations, and Trust and Safety teams to improve high-quality content supply, creator value, spending efficiency, transparency, and the scalability of our creator ecosystem. We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. Responsibilities - Design, develop, and maintain backend services for TikTok PGC Creator Strategy and creator monetization, including the Creator Rewards Program, incentive mechanisms, creator experiences, governance, and payout. - Build reliable and scalable systems that translate creator strategy into configurable eligibility, reward calculation, experimentation, governance, and financial workflows. - Partner with Product, Data Science, Research, Operations, and Trust and Safety teams to understand creator and business needs, evaluate trade-offs, and deliver well-designed technical solutions. - Improve the correctness, performance, availability, observability, and data integrity of large-scale, data-intensive systems through testing, monitoring, code reviews, and technical documentation. - Contribute to technical design and implementation, take ownership of projects from development through launch, and use data and feedback to drive ongoing product and system iteration.

Qualifications

Minimum Qualifications - Individuals who are completing or have recently completed a Bachelor's degree in Computer Science or a related discipline. - Proficiency in at least one backend programming language such as Go, Java, C++, or Python; experience with Go is a plus. - Solid understanding of data structures, algorithms, computer networks, operating systems, and database fundamentals. - Familiarity with relational databases and caching technologies such as MySQL and Redis, including basic indexing and performance optimization concepts. - Strong problem-solving skills, learning agility, ownership, and the ability to communicate and collaborate effectively in a team environment. Preferred Qualifications - Hands-on software engineering experience through internships, research, open-source contributions, coding competitions, or relevant projects. - Experience with backend services, distributed systems, microservices, message queues, RPC frameworks, or cloud-native technologies. - Exposure to high-concurrency or data-intensive systems and an understanding of reliability, observability, and data consistency. - Interest in the creator economy, monetization products, recommendation ecosystems, or trust and safety systems. - High levels of curiosity, creativity, and the ability to solve ambiguous problems in a fast-moving environment.

Job Information