Knit provides an AI-native, end-to-end consumer research platform that combines quantitative and qualitative surveys with researcher-driven generative AI to automate analysis and deliver report-ready insights for enterprise teams.
<h3><span style="color: rgb(18, 152, 138);"><strong>A little about us… </strong></span></h3> <p><a href="https://goknit.com/"><strong>Knit</strong></a> is the AI-native consumer research platform helping brands automate and accelerate primary research. With our Researcher-Driven AI, we’ve condensed the entire quant + qual research process from weeks into days (sometimes hours!) for 50+ enterprise brands — including Amazon, T-Mobile, Mars, NASCAR, and more. We’re on a mission to scale and democratize world-class research. From survey generation to stakeholder-ready reports, our platform is redefining how insights teams operate — and we need your help to push the limits of what’s possible.</p> <h3><span style="color: rgb(18, 152, 138);"><strong>Overview</strong></span></h3> <p>We're hiring a Lead Product Manager to help redefine what customer understanding looks like in an AI-native world. You'll own a meaningful product surface end-to-end, drive company-level bets, and operate as a senior voice in how Knit thinks about product strategy, AI craft, and customer value.</p> <p>You'll ship in two-week cycles alongside one of the strongest engineering benches you'll find at this stage. You'll partner closely with our Director of Product, CTO, CEO, on-staff PhD-level Researchers, and Engineering Leads. This is a force multiplier role in a senior-heavy team, and at this level, we expect your judgment and conviction to shape not just what you ship, but what Knit becomes.</p> <h4>Outcomes</h4> <p>Success in this role is defined by sharper product decisions, stronger execution, and measurable customer and business impact on the surface you own.</p> <ul> <li><strong>Customer adoption of shipped work:</strong> Usage and adoption rates of new and materially updated capabilities within our target ICP.</li> <li><strong>Product velocity and roadmap reliability:</strong> Consistent shipping against outcome-driven commitments, with fewer mid-stream changes and clearer scope on what's in vs. out.</li> <li><strong>Customer and business impact:</strong> Expansion revenue, win rate, retention, and customer value creation attributable to your product work.</li> <li><strong>Cross-functional coherence:</strong> Engineering, Research, and GTM operating from one shared reality about what matters most, and why.</li> <li><strong>Strategic contribution:</strong> Bets you've brought to the table, backed by customer conviction and market insight, that shaped the roadmap beyond your own surface.</li> </ul> <h3><span style="color: rgb(45, 194, 107);"><strong><span style="color: rgb(18, 152, 138);">Responsibilities | What you will own...</span><br></strong></span></h3> <p><strong>Primary responsibilities of this role:</strong><strong><br></strong></p> <ul> <li><strong>Own a Meaningful Product Surface End-to-End</strong><strong><br></strong>Drive the full lifecycle of your product surface, from discovery to delivery to adoption. Write crisp specs, prioritize ruthlessly, and partner with engineering. Own outcomes, not outputs. At this level, we expect you to define the surface you’re working on in addition to executing against it.</li> <li><strong>Build Direct Customer Intuition</strong><strong><br></strong>Spend meaningful, consistent time with customers. Work alongside our PhD-level Researchers, but bring your own developed point of view on how users and buyers at Fortune 1000 brands think, what they need, and where the market is moving.</li> <li><strong>Make AI-Native Product Decisions</strong><strong><br></strong>Own the AI layer of your surface: eval strategies, quality loops, failure-mode design, when to trust the model versus defer to humans. This is what separates us from AI-washed research tools, and you'll help us defend and extend that gap.</li> <li><strong>Operate as a Force Multiplier Across R&D and GTM</strong><strong><br></strong>Drive clarity on tradeoffs, eliminate mid-stream thrash, and ensure Engineering, Research, and GTM are working from one shared reality about what matters and why. At this level, we expect you to <em>create</em> alignment.</li> <li><strong>Contribute to Company-Level Decisions & Roadmap</strong><strong><br></strong>Your impact should reach well beyond what you ship. Bring bets to the betting table backed by real customer conviction, competitive insight, and business judgment. Weigh in on how we plan quarters, how we position against competitors, and how we tell our story to customers. See your bets through with evidence, judgment, and taste.</li> </ul> <h3><span style="color: rgb(18, 152, 138);"><strong>Required Skills & Experiences</strong></span></h3> <p><strong>Required:</strong></p> <ul> <li><strong>7+ years as a Product Manager</strong>, including meaningful time at a company known for strong product culture — where you learned what a great product org looks like from great leaders, and where you were trusted to operate with real autonomy.</li> <li><strong>0→1 experience.</strong> You've taken a product from zero to meaningful customer usage. Ideally, in an early-stage environment (seed/Series A), where you didn't have a full supporting cast to lean on.</li> <li><strong>AI-native fluency.</strong> You've shipped LLM-based features in production. You understand evals, hallucination management, latency/cost tradeoffs, and failure-mode design — even if you didn't write the eval code yourself. You use AI tools fluently in your own PM work to draft, prototype, research, and design. You have a real, developed point of view on how the PM role is changing in an AI-native world.</li> <li><strong>Exceptional written and verbal communication.</strong> Clarity under compression is a baseline expectation. At this level, you're also helping set the standard for how the team communicates.</li> <li><strong>Strong technical fluency. </strong>Comfortable driving real conversations with senior engineers about architecture, tradeoffs, and constraints — not just translating between the