Staff Backend Engineer, Core Data Service

The TikTok Datastore Service team designs, builds, and governs the core online storage infrastructure that powers our global products. Our mission is to provide data services with ultimate performance, reliability, and intelligence for hundreds of millions of users and countless business scenarios worldwide. Here, you will tackle world-class challenges in globalization, multi-region active-active architecture, compliance, and cost efficiency, while leveraging AI to drive the evolution of next-generation storage architecture.
Responsibilities
- Lead the architectural design and evolution of the core data service in a global context. Drive the design and implementation of complex solutions for active-active architecture, cross-region data consistency, and high availability, ensuring world-class stability and scalability.
- Engage deeply in the development of core metadata management, storage, and distribution systems. Continuously optimize for performance to guarantee extreme efficiency under trillion-level data scales and tens of millions of QPS.
- Explore and drive the deep integration of AI technologies with core data services. Apply an AI-Native mindset to design and implement innovative solutions such as intelligent data insights, AI-assisted architecture governance, and anomalous pattern detection to enhance system intelligence and automation.
- As a domain expert, analyze business needs and technology trends to define the medium-to-long-term technical roadmap for data services, and lead the team to overcome key technical challenges.
Requirements:
Minimum Qualifications
- Bachelor's degree or higher in Computer Science or a related field, with 5+ years of experience in developing large-scale backend distributed systems.
- Extensive hands-on experience in designing and implementing globalized, active-active architectures, with a deep understanding of the associated challenges and proven solutions.
- Proficiency in at least one mainstream backend language (e.g., Go, C++, Java) with strong coding skills, a commitment to clean code, and an AI-Native coding mindset.
- Proven ability to lead the design and successful delivery of complex distributed systems projects with demonstrable results.
Preferred Qualifications
- Practical experience with AI-Native systems or AIOps; a proven track record of applying AI/ML technologies to the infrastructure domain is a strong plus.
- In-depth understanding of the principles of, or source-level contributions to, at least one distributed storage system (e.g., Redis, RocksDB, Spanner).
- A strong passion for technology, with excellent problem-solving, communication, and collaboration skills.