MongoDB
Senior Product Manager, Search Platform
MongoDB, San Francisco, California, United States, 94199
Senior Product Manager, Search Platform
– New York or San Francisco Preferred (Hybrid) – Remote Optional (North America)
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, mastering concepts like CAP theorem, consistency models, and sharding strategies, backed by real‑world empathy for the engineering experience.
Strategic Vision at the Technical Edge: Operate comfortably at the intersection of complex architecture and business strategy, capable of debating consensus algorithms with engineers while driving data‑driven storytelling that connects infrastructure health to critical business outcomes.
Unrivaled Influence: Earn the trust of senior engineers through technical depth and respect for complexity, guiding architectural decisions without formal authority and translating those decisions into market differentiation and forward‑looking product investments.
Visionary Customer Obsession: Understand that for platform products, your customers build abstractions on top of yours, designing 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 and debate replication flows and consistency guarantees with Staff Engineers.
State of Reliability: Deliver a report identifying the top 3 sources of operational toil and observability blind spots.
The Quick Win: Identify and ship one low‑hanging reliability improvement (e.g., a missing metric or documentation gap) to demonstrate immediate value to the engineering team.
Month 6
Operationalize SLOs: Partner with SRE to publish official SLOs/SLIs, shifting the culture from "is it down?" to managing error budgets.
The "Conviction Paper": Synthesize customer discovery into a strategic white paper defining the architectural investments needed for the next 18 months.
Observability Upgrade: Lead the rollout of high‑signal alerting strategies that move the team from reactive triage to proactive prevention.
Month 12
Quantifiable Health Gains: Demonstrate measurable improvement in system metrics (e.g., reduced p99 latency, improved MTTR, or 0 capacity‑related incidents).
Tier‑1 Launch: Successfully guide a major infrastructure capability (e.g., new vector index or sharding mechanic) from concept to General Availability.
Authority: Establish yourself as the internal authority on search scaling, influencing roadmap allocation toward long‑term platform health.
About MongoDB MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI.
Equal Employment Opportunity MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
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– New York or San Francisco Preferred (Hybrid) – Remote Optional (North America)
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, mastering concepts like CAP theorem, consistency models, and sharding strategies, backed by real‑world empathy for the engineering experience.
Strategic Vision at the Technical Edge: Operate comfortably at the intersection of complex architecture and business strategy, capable of debating consensus algorithms with engineers while driving data‑driven storytelling that connects infrastructure health to critical business outcomes.
Unrivaled Influence: Earn the trust of senior engineers through technical depth and respect for complexity, guiding architectural decisions without formal authority and translating those decisions into market differentiation and forward‑looking product investments.
Visionary Customer Obsession: Understand that for platform products, your customers build abstractions on top of yours, designing 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 and debate replication flows and consistency guarantees with Staff Engineers.
State of Reliability: Deliver a report identifying the top 3 sources of operational toil and observability blind spots.
The Quick Win: Identify and ship one low‑hanging reliability improvement (e.g., a missing metric or documentation gap) to demonstrate immediate value to the engineering team.
Month 6
Operationalize SLOs: Partner with SRE to publish official SLOs/SLIs, shifting the culture from "is it down?" to managing error budgets.
The "Conviction Paper": Synthesize customer discovery into a strategic white paper defining the architectural investments needed for the next 18 months.
Observability Upgrade: Lead the rollout of high‑signal alerting strategies that move the team from reactive triage to proactive prevention.
Month 12
Quantifiable Health Gains: Demonstrate measurable improvement in system metrics (e.g., reduced p99 latency, improved MTTR, or 0 capacity‑related incidents).
Tier‑1 Launch: Successfully guide a major infrastructure capability (e.g., new vector index or sharding mechanic) from concept to General Availability.
Authority: Establish yourself as the internal authority on search scaling, influencing roadmap allocation toward long‑term platform health.
About MongoDB MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI.
Equal Employment Opportunity MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
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