Workplace
On-site
Employment
Full-Time
Published
Jul 29, 2025
Closes
No date supplied
The role
About the Team: The Database Systems team specializes in high-performance distributed databases. Our team built Rockset, the real-time search, analytics, and vector database that powers all vector search and retrieval augmented generation (RAG) at OpenAI. In addition to retrieval, as an online database, Rockset powers core functionality across all of OpenAI's product lines and many critical internal use cases. About the Role: We are looking for engineers passionate about distributed systems, close-to-the-metal performance optimization (our core engine is written in C++), and building scalable database infrastructure from the ground up. As an engineer on the Database Systems team, you'll contribute to the core database engine, driving improvements across ingestion, query execution, indexing, and storage. You'll partner with teams across OpenAI to unlock new product capabilities and help scale online database reliability and throughput as usage grows by orders of magnitude. In this role you will: - Design, build, and operate high-performance distributed systems - Identify and resolve performance bottlenecks to scale infrastructure to the next order of magnitude - Define long-term technical direction and guide system evolution - Collaborate with product, engineering, and research teams to deliver scalable and reliable infrastructure - Dig deep into complex production issues across the stack - Contribute to incident response, postmortems, and best practices for system reliability You might thrive in this role if you: - Have significant experience building, scaling, and optimizing distributed systems at scale - Are curious about database internals, storage engines, or low-latency query systems - Enjoy debugging challenging performance issues in complex, high-throughput systems - Have experience operating production clusters at scale (e.g., Kubernetes or other orchestration systems) - Think rigorously about scalability, correctness, and reliability - Thrive in fast-paced
Requirements
Department: Applied AI; Team: Applied AI Infrastructure