MongoDB
Staff Product Manager, AI Builder Experience
United States · Staff+
Sponsorship not specified$151k-$297kDetected 16 hours ago
Distributed SystemsMongoDBAWSGCPCloud PlatformsOAuthAgentic AIIncident ResponseProduct ManagementProduct StrategyLeadershipCommunication
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odds of building a lasting career here
64Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →Employer immigration record
from this employer's Department of Labor filings
Green-card intent detected
MONGODB, INC. obtained a prevailing wage determination for Software Developers in San Francisco, CALIFORNIA on 2026-06-29. No matching green-card filing appears in our data yet. The determination expires in 21 days (2026-09-26), and a green-card filing must follow before then or the employer starts over.
Green-card follow-through: 59%
Of 17 labor certifications old enough to have been used, 7 expired without the employer filing the next step. Median time from filing to decision: 495 days.97% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.
Files H-1B transfers
16 transfer filings in the last year, covering 16 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
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About the role
- We help human developers and coding agents discover, evaluate, and choose MongoDB, and we make MongoDB work naturally inside the AI-native tools, frameworks, and platforms where software is being built.
- You will make those three parts work together so MongoDB becomes the obvious database choice wherever AI-native software is created.
Responsibilities
- Turn partner and customer needs into clear product bets, sequencing near-term delivery against a compelling long-term platform strategy
- Build the next phases of the Partner API, including self-serve onboarding, enterprise and administrator controls, partner-managed account creation and billing, partner discovery, and a high-quality integration bar
- Work directly with strategic AI-native partners, cloud platforms, and similar to understand their users, business models, technical constraints, and adoption levers
- Represent ABX and MongoDB externally as a credible voice on AI-native product development, developer ecosystems, and partner platforms
- 8+ years of product management or equivalent experience, including ownership of complex technical products, platforms, APIs, developer tools, ecosystems, or partner integrations
Requirements
- Strong analytical judgment and the ability to define meaningful outcomes even when the direct revenue line is indirect or still emerging
- Deep technical fluency: you can reason about APIs, authentication and authorization, distributed systems, platform boundaries, integrations, data flows, reliability, and security trade-offs
- Partner deeply with the Partner team, IAM, Billing, Security, Engineering, Design, Docs, Analytics, Product Marketing, Sales, and Technical Services to align all towards the cross-functional outcomes required
- Ensure the platform works for both human and agentic developers: APIs and tools must be understandable to people, usable by agents, observable, secure, and resilient under automation
Nice to have
- Experience with partner platforms, marketplaces, developer ecosystems, cloud platforms, databases, infrastructure, or enterprise SaaS
- Experience with OAuth, delegated access, API governance, partner billing, provisioning, or multi-tenant product models
- Experience with MongoDB, developer tools, application frameworks, or data infrastructure
- Present a clear recommendation for the long-term Partner Platform shape, including the investments, sequencing, and trade-offs required to make MongoDB the default database for AI-native builders
- Success Measures
- Produce a concise current-state assessment: what is working, what is fragile, what is one-off, and what must become platform capability
Skills
- AI Builder Experience (ABX) is MongoDB's front door for the agentic era.
- Staff Product Manager to own the Partner Platform:
Compensation
- Salary is one part of MongoDB's total compensation and benefits package.
- Please note, the base salary range listed below and the benefits in this paragraph are only applicable to U.S.-based candidates.
- MongoDB's base salary range for this role in the U.S. is:
Benefits
- Own the vision, strategy, and roadmap for the MongoDB Partner Platform, starting with the Partner API and evolving toward a scalable, self-serve industry leading partner experience
- Establish a repeatable operating model for partner intake, design-partner engagement, integration support, launch readiness, documentation, incident response, and post-launch learning
- Other benefits for eligible employees may include:
Company info
- With offices worldwide and over 67,000 customers, including AI-native startups and approximately 75% of the Fortune 100, relying on MongoDB for their most important applications, we're powering the next era of software.
- Define the metrics that show whether the platform is creating value, e.g. partner activation, time to first successful integration, integration quality, end-user adoption, successful agentic workflows, cluster growth, and partner-influenced revenue
- Create clear product narratives and communicate strategy to executives, engineering teams, partners, customers, and field stakeholders
- What We're Looking For
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This listing is sourced directly from MongoDB's careers page and normalized into a canonical job model.