Founding Product Manager

TL;DR: As our Founding Product Manager, you’ll own core parts of the product that power this experience end-to-end: how teams ask questions, how AI designs and runs research, and how insights are synthesized and delivered into decision-ready outputs. You’ll operate in a true 0 to 1 environment, partnering closely with engineering, design, research, and GTM to turn an ambitious vision into a scalable, compounding product.

This is a high-ownership role for someone excited to build a foundational product surface area at the intersection of AI, customer research, and real-world decision-making.

Background

Listen Labs is an AI-powered research platform that helps teams uncover insights from customer interviews in hours, not months. We help customers analyze conversations, surface themes, and make faster, smarter product decisions.

Company highlights that were entirely product-led:

• World-Class Team: Founded by serial entrepreneurs (previous AI exit), former co-founders, and talent from Jane Street, Twitter, Stripe, Affirm, Bain, Goldman Sachs, and many more Sequoia-backed startups (plus IOI/ICPC backgrounds).

• Hypergrowth: We're a fast-growing team backed by top-tier investors that's grown several-fold in the past year, and we're set on multiplying that again. We move fast, care deeply about craft, and love working with people who take ownership.

• Traction: Rapid growth across segments with enterprise wins at Google, Microsoft, Nestlé, and P&G.

• Performance: Industry-leading win rate driven by a highly differentiated product.

• Market Validation: Consistently winning customers across all segments with over six-figure lands that lead to quick expansions.

• Viral Product: Interviews are shared with tens of thousands of viewers, fueling PLG, organic expansion, and daily inbound from Fortune 500s.

Technical Challenges

1. McKinsey On Demand: Building a research agent
   Hiring McKinsey is different than buying software. You don't just get tools, but get opinions, experience, and execution. We build Listen with that perspective: You have an AI agent on your side that knows everything about our platform and the best research practices. It helps you set up your project, conduct interviews with your goals in mind, and analyze thousands of responses.

2. Database of Humanity
   One of the key value props is our ability to find the people you are looking for (eg, "power users of ChatGPT and Excel"). We are building a database of millions of humans. The more studies you do with Listen, the better we understand you. This enables finding people with unmatched accuracy and, in the long run, extrapolating what a person would say based on all previous conversations -- imagine answering questions for your best friend.

3. Realtime Video Interviews
   The next version of our AI interviewer will have emotional understanding of video and voice to read between the lines. The goal is to make our interviewers more nuanced and effective than the most senior user researchers. This involves computer vision, speech analysis, and real-time decision making.

4. Distributed Information Mining
   The most interesting information is not publicly accessible on the web; it lives only in people's minds. We are building an agent that, given a question, finds the right people to talk to, asks the right questions, and returns a report and actionable recommendations. That's what consultants charge millions for. The ceiling is incredibly high, and we are pushing the technical boundaries to help companies, from investment firms to tech companies, make the best decisions.

5. Customer Preference Model & Synthetic Personas
   We're bringing Jeff Bezos' vision of the customer being part of every life decision to life. We're building the most profound understanding of customers, which will allow us to extrapolate to new questions via synthetic personas. This involves complex modeling of human behavior, preferences, and decision-making processes.

What You’ll Do

• Self-Serve Growth

• Own the evolution of Listen’s self-serve motion alongside our enterprise business

• Define high-leverage self-serve use cases and ideal customer journeys

• Identify friction across onboarding, activation, and usage

• Drive product changes that unlock a scalable path to $[XX]M+ in self-serve revenue

Who You Are

• Entrepreneurial and independent: Thrives in ambiguity and thrives when building from scratch.

• Experienced: Typically 5 - 8+ years in product management, startup/early-stage experience, with a track record of launching successful products. Founder background or strong ownership experience is a plus.

• Technically fluent: Comfortable working closely with engineering teams; ability to understand and synthesize technical tradeoffs. Technical degrees or equivalent experience strongly preferred.

• Data-driven and user-centric: Uses metrics, experimentation, and user insight to guide decisions while balancing long-term strategy with short-term learning.

• Excellent communicator: Effectively aligns internal teams and presents strategy to stakeholders across engineering, research, leadership, and external partners.

• Flexible and curious: Quick learner comfortable navigating evolving product domains such as AI, data pipelines, dev tools, or RL environments.

What You’ll Bring

• Strong strategic thinking paired with practical execution skills.

• Proven ability to take ownership and drive broad outcomes with limited structure.

• A passion for building products with real impact and a bias for action.

Life at Listen Labs

• Competitive Compensation: We're backed by world-class investors, including Sequoia Capital, Ribbit, and Conviction, alongside Evantic, AI Grant, and Pear VC, and offer competitive compensation packages with meaningful equity ownership in a market where over 30B has been created in adjacent industries (Medallia, AlphaSense, GLG, Ipsos, Kantar). Our Sequoia partner, Bryan Schreier, was the first investor in Qualtrics - a $12B company tackling similar problems to ours.

• The base range for this role is $175,000 - $280,000. Actual compensation is influenced by a wide array of factors, including but not limited to skill set, experience, and work location. If this range doesn't match your expectations, we still encourage you to apply.