Product Manager, Lab

📋 Description

• • Are you a visionary Product Manager with a passion for exploring the uncharted territories of technology and its potential to revolutionize industries? Fundraise Up is seeking a pioneering Product Manager to lead our innovative 'Lab' initiative, a dedicated space for high-risk, high-upside product exploration. This is a unique opportunity to shape the future of digital fundraising by identifying and validating bold, unconventional ideas that lie beyond the immediate scope of our core platform.
• • At Fundraise Up, we are committed to empowering nonprofits to raise more funds through exceptional donation experiences. Our cutting-edge technology already facilitates millions of dollars in donations monthly for impactful organizations globally. As we continue to scale our core offerings, we are strategically investing in groundbreaking product bets that have the potential to redefine the fundraising landscape. The Lab is at the forefront of this strategic investment, tasked with discovering and nurturing these next-generation capabilities.
• • As the Product Manager for the Lab, your primary mission is to systematically explore, rigorously validate, and effectively de-risk novel product opportunities. These opportunities may not always appear as direct extensions of our current services, demanding a creative and forward-thinking approach. Your success will be measured not by the volume of features shipped, but by the speed of your learning and the quality of your decision-making. You will be empowered to own ideas from their nascent stages through to critical investment decisions: scale, pivot, or kill. The expectation is that most ideas will be terminated early, with only the most promising graduating to our core or new market teams with robust evidence.
• • Your responsibilities will encompass identifying emerging opportunities driven by new technologies, artificial intelligence, evolving data landscapes, advanced platform capabilities, or significant infrastructure shifts. You will translate nascent signals and technical possibilities into clear, actionable product hypotheses. Crucially, you will explore these ideas even in the absence of a defined buyer, a clear market category, or an explicit demand signal. Maintaining a dynamic exploration backlog, meticulously documenting risks, assumptions, and learning objectives, will be key to your process.
• • A significant part of your role involves designing experiments and defining stringent kill criteria before any development begins. You will frame experiments around the single riskiest assumption, ensuring maximum learning efficiency. The choice of experimental fidelity—whether a low-fidelity prototype, a technical spike, a wizard-of-oz setup, or a live pilot—will be strategic, always aiming to build just enough to learn, and no more. This agile approach ensures rapid iteration and minimizes wasted effort.
• • You will be responsible for executing fast, scrappy experiments and pilots with minimal scope. Close collaboration with Engineering, Design, Data, and Go-to-Market teams will be essential during these experimental phases. Ruthless prioritization of learning speed over premature optimization will be paramount to maintaining momentum and extracting maximum insights.
• • Making clear, data-informed investment decisions is a core tenet of this role. You will synthesize experimental results into opinionated recommendations: Scale, Iterate, or Kill. Clear and concise communication of what was tested, what was learned, and what uncertainties remain will be vital. The goal is to avoid 'zombie initiatives' by ensuring every experiment culminates in a decisive outcome, and to have the courage to terminate your own ideas when the evidence suggests they are not viable.
• • When an opportunity demonstrates strong potential, you will prepare it for a clean handoff to the relevant team. This includes presenting validated value and problem hypotheses, comprehensive evidence from experiments or pilots, clearly defined risks, assumptions, and success metrics, and a proposed ownership and scaling model. The Lab's mandate is exploration; it does not run scaled products, ensuring a clear division of responsibilities.
• • Operating with transparency and sharing learnings across the organization is crucial. You will maintain a visible Lab portfolio showcasing ongoing explorations, their rationale, and current signals. Publishing decision memos and learning summaries, and openly sharing insights from failed experiments when valuable lessons are learned, will foster a culture of continuous improvement and knowledge sharing.
• • Leveraging AI to accelerate learning is a key focus. You will utilize modern AI tools to expedite research, synthesis, prototyping, and experimentation. Exploring AI-enabled product ideas with a realistic assessment of costs, latency, data requirements, and accuracy will be essential. Distinguishing genuine capability shifts from mere hype and helping others understand the true impact of AI on learning will be a significant contribution.
• • Finally, you will selectively launch high-risk, high-signal initiatives, even when short-term adoption is uncertain. These launches will be treated as genuine product bets, not mere demonstrations. They will serve to test future categories, shape market perception, and signal technical leadership, with the intent clearly articulated as learning, creating optionality, or external signaling.