Join our MongoDB Search Systems Engineering team at the forefront of building next-generation database infrastructure at scale. You'll work alongside some of our most talented and deeply technical engineering teams who are architecting distributed systems that power highly performant search and AI applications for enterprise customers worldwide. This team operates at the intersection of infrastructure innovation and customer impact—building the foundational platform capabilities that will define how organizations leverage search and AI at scale for years to come.
In this role, you'll serve as both strategic partner and technical translator, helping brilliant engineers navigate the path to operational excellence while maintaining the forward vision to anticipate market needs 18-24 months ahead of current development cycles.
What Makes This Role Unique: This is about architecting the future of search infrastructure. You'll be working with engineers who live and breathe distributed systems, helping them channel that brilliance toward platforms that don't just work today, but anticipate the architectural needs of tomorrow's AI-native applications. If you light up at the challenge of seeing around corners in infrastructure and can hold your own in technical debates about consensus protocols while keeping the team focused on customer value—this is your role.
This role can be based out of our San Francisco office or remotely in USA region.
Role Responsibilities
•Contribute to the Future of Search Infrastructure: Drive the long-term technical vision for MongoDB Search, anticipating emerging patterns in vector, hybrid, and AI-native applications to build conviction around platform investments 12–18 months ahead of market demand
•Champion the Customer & Innovation: Act as the voice of customers building mission-critical AI applications, using deep technical discovery to uncover latent needs around scalability and consistency, ensuring our architecture leads the industry in performance and multi-tenancy
•Drive Engineering Strategy & Impact: Partner deeply with engineering leadership to translate complex technical tradeoffs into business value, balancing rapid innovation velocity with the rigorous production stability required for long-term platform health
•Orchestrate World-Class Observability: Collaborate with SRE and Solutions Architects to build advanced instrumentation strategies and feedback loops, turning production signals and incident learnings into proactive improvements that secure system resilience
Requirements
•Deep Technical Authority: 5+ years of PM experience with a specific focus on infrastructure or distributed systems. You possess a mastery of concepts like CAP theorem, consistency models, and sharding strategies, backed by real-world empathy for the engineering experience—whether that’s being on-call or debugging production incidents
•Strategic Vision at the Technical Edge: You operate comfortably at the intersection of complex architecture and business strategy, capable of debating consensus algorithms with engineers while Data-Driven Storytelling: A proven track record of driving operational excellence combined with exceptional narrative skills. You effortlessly pivot from analyzing low-level system metrics to crafting executive narratives that connect infrastructure health to critical business outcomes
•Unrivaled Influence: You earn the trust of senior engineers through technical depth and respect for complexity, not just title. You excel at guiding architectural decisions without needing formal authority helping to translate those decisions into market differentiation and forward-looking product investments
•Visionary Customer Obsession: You understand that for platform products, your customers are often building abstractions on top of your abstractions, and you design deeply technical products with their long-term success criteria in mind
Nice to Have
•Direct experience with search technologies (Elasticsearch, Solr, Lucene) or vector databases, particularly in production environments at scale
•Experience with AI/ML infrastructure or building platform capabilities that enable AI applications (vector search, embeddings management, hybrid retrieval systems)
Success Measures
Month 3:
•Technical Immersion: Complete a full architectural audit of the search stack. Be able to debate replication flows and consistency guarantees with Staff Engineers
•State of Reliability: Deliver a report i