Staff Product Manager, AI Builder Experience

MongoDB has an opening for a Staff Product Manager, AI Builder Experience, based in New York. The job is full-time and office based. MongoDB has not published a salary for this role, so it is worth asking about pay early in the process.

MongoDB describes the job as follows.

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

Common questions

Is pay published for the Staff Product Manager, AI Builder Experience role?

MongoDB has not included pay in the posting.

Is this a remote, hybrid or office job?

No, it is an on-site job in New York.

What experience do I need for this Staff Product Manager, AI Builder Experience job?

The posting mentions at least 8 years of relevant experience and skills such as AWS, Azure, Google Cloud and MongoDB. Read the full description above for the complete list.

How do I apply for the Staff Product Manager, AI Builder Experience job?

Use the apply button on this page. It takes you to MongoDB's own application form, so your CV goes directly to their hiring team.

When was this job posted?

MongoDB published the role on September 4, 2026. We check the employer's job board every day and take this page down when the role closes, so if you can read it, the job was still listed at our last check.

Source: MongoDB careers page (www.mongodb.com). Applications go straight to the employer. We check the listing daily and remove it once it closes.