We’re seeking motivated and talented students to help us build the next-generation database platform. As a Product Management Intern at MongoDB, you will work closely with our product managers, user experience designers, and software engineers to bring impactful ideas to life. You will be fully integrated into the team, analyzing user needs, identifying pain points, and advocating for customer-centric solutions. You will draw insights from data, explore technical possibilities with engineers and designers, and translate those learnings into clear product requirements and engaging user experiences. Along the way, you will help shape and communicate product strategy to stakeholders across the organization. We’re excited to offer Product Management internship opportunities across a few teams at MongoDB. Each team focuses on a different part of our product, giving interns the chance to contribute to meaningful projects and learn from experienced product managers. Learn more about the teams below: Atlas PM: The team ensures the lifecycle, reliability, and performance of the Atlas data plane. We build the machinery that orchestrates safe hardware and software rollouts, enabling rapid feature delivery while maintaining stability. Simultaneously, we develop intelligent systems to detect and manage customer workloads through auto-scaling, performance tuning, and auto-healing. Underpinning all operations is our commitment to resilience and recovery, ensuring we can respond to health issues, restore availability, and strictly guarantee data durability. Query PM: The Query Team at MongoDB is responsible for designing, building, and optimizing the core query execution engine and related systems that power data retrieval and manipulation across MongoDB's database platform. This includes developing the query planner and optimizer that translates user queries into efficient execution plans, implementing the runtime execution engine that processes queries against various storage engines, and creating sophisticated indexing strategies and data structures that enable fast data access at scale. Search and AI PM: The Search and AI Team at MongoDB is responsible for designing, building, and scaling the retrieval infrastructure that powers AI-native applications on the MongoDB platform. This includes developing Atlas Vector Search—the semantic search engine that enables similarity matching over high-dimensional embeddings—building full-text search capabilities powered by Lucene, and creating the indexing and query semantics that let developers combine vector, keyword, and structured filters into unified retrieval pipelines. The team sits at the intersection of traditional database systems and modern AI workflows, enabling use cases from RAG-based chatbots to recommendation engines to multimodal search.