Staff Product Manager, AI Builder Experience
MongoDB is hiring a Staff Product Manager, AI Builder Experience in Toronto, Canada. Level rates it ; you can apply on MongoDB.
Level's read on this job
- Works on AI ●●●○ is how Level rates this AI product manager role: the daily work is on AI products, without building the model.
- The posting mentions AI agents, product management and partner api among its tools and skills.
- Level classes it as a senior role.
- MongoDB has 382 other open roles on Level.
AI in this role
Own the vision, strategy, and roadmap for MongoDB's Partner Platform focused on AI builder experiences and partner APIs.
The Role
AI Builder Experience (ABX) is MongoDB’s front door for the agentic era. 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.
We are looking for an outstanding Staff Product Manager to own the Partner Platform: the products, experiences, and operating model that allow ecosystem partners to build trusted, high-quality MongoDB experiences for their users. This includes the Partner API and the broader path toward self-serve integrations, partner onboarding, enterprise controls, marketplace/discovery, and partner-managed experiences.
This is a role at the intersection of humans, machines, and partners. Human builders increasingly work through AI agents; AI agents need reliable interfaces, context, permissions, and tools; and partners determine where those experiences are discovered and adopted. You will make those three parts work together so MongoDB becomes the obvious database choice wherever AI-native software is created.
The role is highly cross-functional and highly visible. You will work with engineering, design, IAM, billing, security, documentation, analytics, product marketing, partnerships, field teams, and strategic customers and partners. You will be expected to operate as both a strategic product leader and a hands-on builder who can turn an ambiguous ecosystem opportunity into a clear product vision, strategy, and an executable roadmap.
What You’ll Do
- 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
- 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
- Establish a repeatable operating model for partner intake, design-partner engagement, integration support, launch readiness, documentation, incident response, and post-launch learning
- 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
- Work directly with strategic AI-native partners, cloud platforms, and similar to understand their users, business models, technical constraints, and adoption levers
- 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
- 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
- Represent ABX and MongoDB externally as a credible voice on AI-native product development, developer ecosystems, and partner platforms
What We’re Looking For
- 8+ years of product management or equivalent experience, including ownership of complex technical products, platforms, APIs, developer tools, ecosystems, or partner integrations
- Demonstrated success taking a product or platform from ambiguous opportunity through launch, adoption, and continued evolution
- Deep technical fluency: you can reason about APIs, authentication and authorization, distributed systems, platform boundaries, integrations, data flows, reliability, and security trade-offs
- Experience building products for developers, technical users, AI-native workflows, or platform ecosystems. Direct experience with AI agents, MCP, agent frameworks, agentic coding tools, or agentic developer platforms is strongly preferred
- A clear point of view on the difference between building for human developers and building for AI agents, including implications for APIs, documentation, tooling, evaluation, observability, and quality
- Strong partner and customer instincts, with experience translating external needs into a product strategy without becoming a collection of one-off feature requests
- Ability to navigate complex and growing organizations, align teams without direct authority, and create momentum when ownership and dependencies are not obvious
- Comfort balancing speed, security, quality, enterprise requirements, and long-term platform health in a fast-moving market
- Strong analytical judgment and the ability to define meaningful outcomes even when the direct revenue line is indirect or still emerging
- Excellent written and verbal communication skills; you write clear documents, make trade-offs visible, and communicate effectively from engineering working sessions to executive reviews
- Genuine enthusiasm for AI-native development and regular hands-on use of AI tools in your own work
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
Success Measures
Within 30 days:
- Develop a deep understanding of the current Partner API, partner pipeline, design-partner experience, dependencies, launch commitments, and known gaps
- Build strong working relationships with engineering, IAM, Billing, Security, Design, Partnerships, Docs, Analytics, Product Marketing, and the adjacent ABX PMs
- Meet key partners and customers and understand the jobs they need the Partner Platform to accomplish for humans, agents, and their businesses
- Produce a concise current-state assessment: what is working, what is fragile, what is one-off, and what must become platform capability
Within 60 days:
- Evolve the Partner Platform vision and strategy, including clear ownership boundaries with AI Interfaces and AI Frameworks
- Establish a metrics framework connecting partner integration quality and adoption to builder activation, Atlas usage, enterprise confidence, and business impact
- Deliver an aligned roadmap for the next phases of Partner API, partner onboarding, enterprise controls, and partner platform capabilities
- Identify the highest-leverage operating-model changes needed to improve partner speed, quality, and repeatability
Within 90 days:
- Drive one or more high-impact improvements that materially improve partner onboarding, integration quality, enterprise readiness, or end-user adoption
- Establish a credible plan for scaling from design partners to a broader ecosystem without relying on bespoke MongoDB-side work for every integration
- Be recognized by engineering, design, partnerships, marketing, and field teams as a trusted product leader and effective cross-functional partner
- 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
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 data platform for the AI era, enabling builders to create, transform, and disrupt industries with software. MongoDB’s unified data platform, the most widely available, globally distributed data platform on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud data platform and is available across AWS, Google Cloud, and Microsoft Azure.
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.
Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB.
To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!
MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.
MongoDB is an equal opportunities employer.
REQ ID: 3273520423
How we rate this
Staff Product Manager, AI Builder Experience at MongoDB rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in AI product manager jobs at this level
Pay
- Typical AI product manager job
- $180k
This posting doesn't list pay. Use the typical AI product manager figure when pay comes up. See AI product manager jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where product management was part of your work. What did you do?
- Tell me about a project where partner api was part of your work. What did you do?
- Tell me about a project where developer experience was part of your work. What did you do?
- Describe a typical day in a role like this one: which parts run through AI directly?
Adapt your resume
- List these exact terms on your resume: AI agents, Product Management, Partner API, and Developer Experience. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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