Senior Product Manager

MongoDB

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Remote

Quick summary

Work type: Remote
Location: San Francisco, CA
Posted: 61 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $195k

$152k $237k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $174,925–$214,900.

Based on 240 similar postings.

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About MongoDB

MongoDB is a leading American software company that develops and provides commercial support for a popular, source-available document database. Designed to handle unstructured and structured data natively, its platform is purpose-built for modern cloud applications, analytics, and AI experiences.

MongoDB currently has 46 open roles on FindRole.

Listed pay typically runs $110,500–$255,000 across 40 roles with salary data.

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At a glance

TL;DR · Senior Product Manager

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The Senior Product Manager joins the Search Systems Engineering team to build next-generation database infrastructure for enterprise search and AI applications. This role involves driving the long-term technical vision for search infrastructure, anticipating patterns in vector, hybrid, and AI-native applications. You will partner with engineering leadership to translate complex technical tradeoffs into business value, champion customer needs regarding scalability and consistency, and orchestrate advanced instrumentation strategies with SRE and Solutions Architects. The position requires mastery of distributed systems concepts including the CAP theorem, consistency models, and sharding strategies. Candidates should possess experience with search technologies like Elasticsearch, Solr, or Lucene, as well as vector databases. You will solve the business problem of balancing rapid innovation velocity with the rigorous production stability required for long-term platform health.

What does a Product Manager earn in California?

Median $222500 from 327 postings across 57 companies.

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Skills

MongoDB Distributed Systems Vector Search Elasticsearch Solr Lucene Vector Databases AI/ML Infrastructure CAP Theorem Sharding Consistency Models SLOs SLIs Observability AWS Google Cloud Microsoft Azure MongoDB Atlas

What you'll do

Drive the long-term technical vision for search infrastructure to anticipate emerging patterns in vector and AI-native applications.
Conduct deep technical discovery to uncover latent customer needs regarding scalability, consistency, and multi-tenancy.
Translate complex technical tradeoffs into business value to balance rapid innovation with production stability.
Build advanced instrumentation strategies and feedback loops to turn production signals into proactive system improvements.
Partner with SRE teams to publish official SLOs and SLIs to manage error budgets effectively.
Synthesize customer discovery into strategic whitepapers defining architectural investments for the next 18 months.
Guide major infrastructure capabilities from initial concept through to General Availability.
Establish internal authority on search scaling to influence roadmap allocation toward long-term platform health.

What we're looking for

5+ years of PM experience with a specific focus on infrastructure or distributed systems.
Mastery of concepts like CAP theorem, consistency models, and sharding strategies.
Ability to translate complex technical tradeoffs into business value and executive narratives.
Proven track record of driving operational excellence and managing low-level system metrics.
Ability to guide architectural decisions and influence senior engineers without formal authority.
Direct experience with search technologies (Elasticsearch, Solr, Lucene) or vector databases (preferred).
Experience with AI/ML infrastructure or building platform capabilities for AI applications (preferred).