Our team is building a cloud-based distributed system responsible for the core components of search including data ingestion, performance, query language, query execution, for both relevance-based search and vector search. Our product is being adopted quickly and there are many interesting projects. This is a visible leadership role where you will be responsible for the technical success of our Search Query interface.
This role is based in our San Francisco office.
You would get to:- Lead complex projects across the MongoDB ecosystem, for instance, co-optimization of approximate nearest neighbor vector search with the MongoDB aggregation framework
- Set initiative level strategy, architect plan, and lead team towards successful execution
- Identify, design, and implement features enhancing our query language, performance, and operability
- Perform code reviews with peers and make recommendations on how to improve our software development processes
- Influence and grow team members through active mentoring, and leading by example
Ideally, you will be:- 8+ years experience in data management systems, specifically with a strong query processing and optimization background. A Master's or Ph.D degree in a related field is a plus
- Professionally experienced with designing high-volume query engines, such as a database, search system, or vector search system
- Experienced in the development and maintenance of stateful distributed systems
- Eager to shape the technological direction of a complex system and have the ability to lead initiatives through collaboration with others
Success Measures:- In 1 month, you will be mostly learning - becoming familiar with our teams, systems and architecture
- In 3 months, you'll contribute to the improvement of our search engine service
- In 6 months, you'll be designing the next generation architecture and roadmap for search query optimization and execution within the MongoDB ecosystem