Top Engineering Jobs in San Francisco, CA

Lead the architecture and technical direction of MongoDB’s next-generation Search and Vector Search infrastructure. Own cross-system data infrastructure, define technical roadmaps, evolve mongot and Mongo Management Service, drive complex multi-team initiatives, make distributed-systems decisions around consistency, durability, scale, and failure modes, and mentor engineers while influencing leadership and global engineering practices.

Develop and maintain Kubernetes runtime environments, support developers, resolve critical issues, and participate in on-call rotations for production systems.

Seeking a Site Reliability Engineer with expertise in networking and distributed systems for building secure multi-cloud infrastructure. Responsibilities include maintaining network architecture and ensuring reliable service-to-service communication, involving a 24/7 on-call rotation.

Design and implement distributed, high-performance search and vector search infrastructure for MongoDB Atlas. Lead architecture and execution of complex projects, improve reliability, performance, security, and autoscaling, perform code reviews, mentor team members, and collaborate across teams to deliver cloud-scale search features.

As a Software Engineer 3, you will design and build core components for a multi-tenant inference platform integrated with MongoDB Atlas, collaborating with ML engineers to enhance performance and reliability.

The Software Engineer will design, build, test, and maintain backend software for Atlas Search, ensuring scalability and system improvement in a collaborative team environment.

Design, implement, and maintain distributed systems software for Atlas Search. Collaborate with the team on scalability improvements, lead projects, and contribute to technical decision-making.

Leads and manages an 8–10-person storage engineering team responsible for MongoDB’s transactional read/write path, durability, availability, performance, indexing, and storage architecture. Owns the roadmap, customer escalations, cross-team initiatives, engineering quality, hiring, coaching, and execution. Partners with Replication, Query, Sharding, Atlas, and other teams on distributed systems and workload-management improvements.

Build and optimize MongoDB’s SQL interface, including query engines, SQL-to-MQL translation, database connectors, and BI integrations. Develop backend systems that improve performance, scalability, reliability, and usability for large datasets and complex queries. Collaborate with product managers and customer experience teams, contribute to roadmap initiatives, resolve bugs, and lead major technical projects.

Join MongoDB's Query Execution team to improve the database's core execution engine, build high-performance query features, and mentor team members. You will drive roadmap initiatives and ensure production-ready code for complex analytical workloads.