Cursor Logo

Cursor

Software Engineer, Storage

Reposted One Month Ago
In-Office
San Francisco, CA, USA
Mid level
In-Office
San Francisco, CA, USA
Mid level
Design and own Cursor's storage layer: databases, caches, and multi-database topology. Build sharding, migrations, query instrumentation, cache infrastructure, and guidance for choosing storage engines to ensure reliability, performance, and scalable operations.
The summary above was generated by AI

Our mission is to automate coding. The first step in our journey is to build the best tool for professional programmers, using a combination of inventive research, design, and engineering. Our organization is very flat, and our team is small and talent dense. We particularly like people who are truth-seeking, passionate, and creative. We enjoy spirited debate, crazy ideas, and shipping code.

About the Role

As a Software Engineer on the Storage team at SpaceXAI, you'll own the data layer that underpins every product surface: the databases, caches, and the strategy for how teams provision, query, and scale their data stores.

Millions of developers depend on Cursor every day, and the future of our storage architecture is one of the highest-leverage problems at the company: get it right, and every team ships faster, every product surface gets more reliable, and SpaceXAI can scale to meet explosive demand. You'll design and execute the path to a robust, multi-database topology built for that growth.

Example projects include...

Designing the next-generation data architecture: evolving our storage layer into a partitioned, resilient topology that keeps pace with SpaceXAI's rapid growth.

Building query attribution and guardrails: instrumenting every database query by service, catching bad patterns before they hit production, and making it impossible to ship problematic queries without review.

Defining the "when to use what" strategy for data stores: creating clear guidance and golden pathways so every team picks the right engine for their workload without second-guessing.

Owning cache infrastructure end-to-end: reliability, capacity planning, and patterns that let product teams move fast without worrying about cache correctness.

You may be a fit if

You have deep experience with relational databases at scale, especially Postgres, MySQL, or similar OLTP systems.

You've tackled database sharding, migration, or decomposition problems in production environments.

You understand the tradeoffs between different storage engines and can help teams make the right choices for their workloads.

You care about operational excellence: backups, monitoring, query performance, and capacity planning are things you think about proactively.

You have strong software engineering fundamentals and enjoy building systems that other engineers depend on.

Applying

If there appears to be a fit, we'll reach out to schedule 2-3 short technicals. After, we'll schedule an onsite in our office, where you'll work on a small project, discuss ideas, and meet the team.

#LI-DNI

Cursor San Francisco, California, USA Office

San Francisco, CA, United States

Similar Jobs

An Hour Ago
In-Office
Sunnyvale, CA, USA
143K-210K Annually
Senior level
143K-210K Annually
Senior level
Cloud • Information Technology • Machine Learning
Design and implement distributed, exabyte-scale S3-compatible object storage for AI workloads. Improve storage reliability, durability, security, observability, throughput, and latency using technologies such as RDMA, GPU Direct Storage, and distributed filesystem protocols. Collaborate with infrastructure, platform, product, and operations teams to deploy and troubleshoot production systems, develop monitoring dashboards, analyze telemetry, and mentor engineers.
Top Skills: CCephClickhouseCloud-Native InfrastructureDaosDistributed FilesystemsFuseGoGpu Direct StorageGrafanaKubernetesNfsObject StoragePrometheusRdmaRustS3
One Month Ago
In-Office
153K-204K Annually
Senior level
153K-204K Annually
Senior level
Cloud • Information Technology • Machine Learning
Design and implement distributed, exabyte-scale storage systems for AI workloads, including S3-compatible object storage and dedicated storage clusters. Improve storage reliability, durability, security, observability, throughput, latency, and resilience using technologies such as RDMA, GPU Direct Storage, and distributed filesystems. Monitor and troubleshoot production systems, develop performance dashboards, analyze telemetry, collaborate across infrastructure teams, and mentor engineers.
Top Skills: CCephClickhouseDaosFuseGoGpu Direct StorageGrafanaKubernetesNfsPrometheusRdmaRustS3
10 Days Ago
In-Office
San Francisco, CA, USA
1-2 Annually
Expert/Leader
1-2 Annually
Expert/Leader
Artificial Intelligence • Natural Language Processing • Generative AI
Lead the strategy, architecture, development, operation, and scaling of Anthropic’s exabyte-scale, multi-cloud storage infrastructure. Design secure, reliable, cost-efficient storage systems; guide migrations; collaborate with cloud, networking, datacenter, research, and business teams; make architectural tradeoffs; improve observability, capacity planning, incident response, and on-call operations; and remain hands-on in critical production code.
Top Skills: Block StorageC++Distributed File SystemsDistributed Storage SystemsGoJavaMulti-Cloud InfrastructureObject StorageObservabilityRust

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account