Staff Software Engineer (Database Systems)

• Design and build core modules of Milvus and Vector Lakebase, including storage, query engine, indexing, load balancing, resource management, and distributed execution

• Drive the evolution of the engine architecture, bringing Lake-native capabilities, elastic scaling, and large-scale multi-tenancy into production to support the next stage of growth

• Design database capabilities for AI and Agent workloads, handling more complex access patterns, higher concurrency, larger scale, and lower latency

• Own the stability of Zilliz Cloud, working closely with cloud platform and product engineering teams to bring engine capabilities into production and using real customer scenarios to drive engine improvements

• Iterate on AI developer tooling, bringing AI into the engineering workflow to improve team velocity and system observability

• Contribute to the Milvus open-source community through design docs, code, code reviews, and technical discussions

Benefits

• Equity

• Regular bonus and equity refresh opportunities

• Comprehensive medical, dental, and vision insurance

• Paid time off, including vacation, bereavement, and sick days

• Generous 401(k) and regional retirement plans

• Hybrid work model/Remote work opportunities available- 3+ years of experience building database systems, distributed systems, storage engines, query engines, search systems, or large-scale data infrastructure

• Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience

• Strong engineering taste: the ability to judge what design is simpler, what abstraction will last, and which performance and cost tradeoffs actually matter

• Strong systems programming ability in one or more of C++, Go, or Rust

• Experience with large-scale cloud-native databases, storage systems, search systems, or data platforms is a strong plus; open-source contributions in databases, storage, search, Kubernetes, or distributed systems are a strong plus

• Deep understanding of distributed systems and database internals, including consistency, scalability, performance, fault tolerance, query execution, storage, indexing, resource management, and engineering tradeoffs