Software Engineer – Global E-Commerce AI Search Infrastructure (TikTok Shop)

About the Team

Search is no longer just a feature—it is the defining battleground that will determine whether TikTok Shop becomes the first truly global e-commerce super-app. Our Search platform is the core engine behind the "shelf-field" (product card) strategy, and the key to competing head-to-head with Amazon, Taobao, and Pinduoduo in a global market worth over $10 trillion.

Search will propel TikTok Shop from tens of billions to hundreds of billions in annual GMV by activating real shopping intent, unlocking zero-sales products, and ensuring every item becomes instantly discoverable the moment a user types or taps.

We innovate where extreme performance, massive global scale, and uncompromising consistency meet.

Responsibilities

You will design, build, and optimize the core infrastructure that supports TikTok Shop’s recall, ranking, and re-ranking pipelines globally.

• Core Search Engine Development: Design and implement high-performance online retrieval systems. Optimize core components including the inverted index, vector retrieval (ANN/HNSW), query understanding, and merger logic.
• Real-Time Data Pipelines: Build highly scalable and fault-tolerant data pipelines using Flink, Kafka, and Spark to ensure product changes (price, stock, and new listings) are reflected in search results in near real-time.
• System Stability & Performance: Drive latency, throughput, and cost optimizations for services handling hundreds of thousands of QPS. Troubleshoot complex distributed system issues, manage cross-region failover, and design high-availability disaster recovery solutions.
• Large-Scale Storage & Retrieval: Design and optimize distributed storage libraries (based on RocksDB/Redis) and columnar databases tailored for high-speed e-commerce feature retrieval.
• ML Infrastructure Collaboration: Work closely with Algorithm/ML Engineers to productionize state-of-the-art Large Language Models (LLMs) , AI Search, and multi-modal search models, ensuring the infrastructure supports massive model serving and real-time feature engineering.

Minimum Qualifications

• Bachelor’s in Computer Science, Computer Engineering, or a related technical field.
• At least 3 years of hands-on experience building large-scale distributed systems, search engines, or low-latency online services.
• Strong coding proficiency in C++, Go, or Java (C++/Go is heavily preferred for core infra roles).
• Deep understanding of computer science fundamentals: Data structures, algorithms, operating systems, network programming, and multi-threading.
• Experience with distributed system technologies, such as RPC frameworks (gRPC/Thrift), Message Queues (Kafka), and Stream Processing (Flink/Spark).

Preferred Qualifications

• Search Internals: Direct experience with search engine internals (e.g., Lucene, Elasticsearch, Solr, Vespa) or building custom inverted index/retrieval systems.
• Vector Search: Experience with vector database technologies or libraries (FAISS, HNSW, ScaNN).
• Storage Engines: Deep understanding of NoSQL and KV stores (Redis, RocksDB, HBase) or columnar storage systems.
• Performance Optimization: Proven track record of reducing p99 latency, optimizing memory usage in C++, or driving measurable efficiency gains in high-traffic systems.
• Domain Knowledge: Experience working in E-commerce, AdTech, or large-scale consumer platforms.