About the Role
We're looking for a Senior Product Manager to help drive the strategic vision, product strategy, and roadmap for the AI Builders Experience Team. The AI Builders Experience team owns how MongoDB shows up for the rapidly growing community of developers building AI-native applications, with explicit license to explore where this space is heading. This includes our integrations with frameworks like LangChain, Mastra, LlamaIndex and others; the patterns and reference architectures we ship for RAG, agents, and semantic search; and the developer-facing tooling that makes MongoDB the natural choice for AI workloads. You'll also place strategic bets on where the space is going next.
Our customer is the AI application builder, and our job is to deliver an exceptional developer experience for that audience. You should be the kind of PM who lives in the AI builder community, continuously tracking emerging frameworks, tooling, and development patterns, and identifying which deserve a place in MongoDB's portfolio.
You're a strong fit if you have already shipped a product or can demonstrate a side-project where developers were the customer and AI was central to the value proposition. Examples include AI developer tooling such as framework integrations, SDKs/APIs, or agent, evaluation, and observability products. You can walk through what you shipped, who used it, what changed for them, and the decisions you owned along the way.
You'll collaborate closely with a globally distributed engineering team and partners across documentation, developer relations, partnerships, and marketing. Your focus is outward: understanding and serving AI builders where they are.
About the team
We are a highly collaborative team of Product Managers, Engineers, Product Analysts, and Product Marketers, working together to make the experience of building with data, and increasingly with AI, easy and enjoyable for developers.
We are a distributed team, stretching from our offices in Dublin and NYC to other locations in Europe, the US, and Canada. Every now and then, we all meet in one place for project kickoffs, workshops, and team events.
The ideal candidate for this role should have
- 5+ years of product management experience with a track record of shipping developer-facing tools, integrations, SDKs, or APIs
- Hands-on experience as a PM who has owned a developer-facing AI product end to end. You can point to a specific product, name the developers who used it, articulate how you moved their experience forward, and describe the strategic and technical tradeoffs you owned along the way
- Working fluency in the modern AI builder stack, including frameworks such as LangChain, Mastra, or LlamaIndex; patterns like RAG, agents, tool use, and evaluation; and the broader landscape of model providers, vector stores, and orchestration tools
- Ideally have commercial/professional experience developing applications in Python (the interviews for this position may include a live coding component meant to showcase your understanding of idioms, patterns, and evolving runtime environments)
- A demonstrated habit of staying ahead of a fast-moving space. You can point to specific emerging tools, techniques, or communities you've tracked recently, and have a defensible opinion on which matter and why
- Familiarity with adjacent ML and Data Science concepts and tooling (e.g., Pandas, NumPy, common ML frameworks) and an understanding of how AI applications are built, deployed, and monitored in production
- Comfort with the unique challenges of AI product development (model uncertainty, evaluation difficulty, longer or non-linear development cycles) and the ability to set realistic expectations with stakeholders accordingly
- Ability to translate complex technical concepts into clear product direction for a wide range of audiences, from individual developers to executive stakeholders
- Ability to distill customer use cases into comprehensive business cases and execute on them
- A commitment to fostering an inclusive and respectful work environment in line with MongoDB's Core Values
Position Expectations
- Explore the problem space, build connections with your customer base, interact with users in the AI builder community, and formulate the vision, strategy, and roadmap for your area, keeping it aligned with MongoDB's strategic priorities
- Identify and pursue emerging opportunities in the AI builder space (new frameworks, patterns, partnerships, and use cases) and make evidence-based bets on where MongoDB should invest
- Deeply understand all aspects of the business. Your job is to ensure a business outcome, not just product definition
- Work closely with engineering and product marketing to design, ship, and position new capabilities of the MongoDB AI builder experience
- Collect and analyze data that drives product decisions, including signals from community channels, telemetry, partnerships, and direct customer engagement
- Work with thought leaders across the AI ecosystem (framework maintainers, model providers, open-source contributors) to establish credibility and weigh in on discussions shaping the space
- Engage in go-to-market activities such as collaborating on marketing campaigns, running surveys, presenting at conferences, and producing sales messaging
Success Measures
- In three months, you will have onboarded onto current MongoDB technologies and tools, built and shipped a public AI application with Python and MongoDB on GitHub, successfully triaged new issues with the engineering team, taken ownership of the existing roadmap and product backlog, and started building relationships across the globally distributed team.
- In six months, you will have refined existing user stories and JIRA issues, prioritized and started executing on them with your engineering team, and produced a research-backed point of view on emerging opportunities in the AI builder space that informs the roadmap.
- In nine months, you will have produced at least two General Availability releases, integrations or capabilities serving AI builders, delighted users with new and improved experiences (with metrics you've defined to measure customer success), identified new opportunities and refined your roadmap, contributed to adjacent projects, presented to customers, and gained strong support from your team and other stakeholders.