Member of Technical Staff, Product

Overview We are expanding our engineering team to support a strong 6-month product roadmap. We are seeking a highly technical engineer who wants to build a product that changes how companies make decisions and tackle complex problems end-to-end. 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 — 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 are a fast-growing team backed by top-tier investors. We move fast, care deeply about craft, and value 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 McKinsey On Demand: Building a research agent. We provide an AI agent that knows everything about our platform and the best research practices to help you set up projects, conduct interviews, and analyze thousands of responses. Database of Humanity: Building a database of millions of humans to find the right people and, over time, extrapolate what a person would say based on historical conversations. Realtime Video Interviews: The next version of our AI interviewer will have emotional understanding of video and voice, enabling more nuanced and effective interviews through computer vision, speech analysis, and real-time decisions. Distributed Information Mining: Creating an agent that finds the right people to talk to, asks the right questions, and returns reports and actionable recommendations. Customer Preference Model & Synthetic Personas: Building deep models of customer behavior to extrapolate insights via synthetic personas. What We Look For You want to solve problems end-to-end: Engineers own parts of the product and make decisions across the LLM pipeline, infrastructure, backend, and UX with help when needed. You have a high bar for quality: Move fast, but care about output, details, and building reliable products—especially in AI. You want to push LLM capabilities: Work with advanced AI models and partner with foundational companies on new releases. You are a clear thinker and communicator: Expect to share tradeoffs, problems, and blockers directly in a minimal-meeting culture. You are highly technical: Our team includes individuals with deep interests in language design, compilers, and related areas. Life at Listen Labs Compensation and Benefits: Competitive packages with meaningful equity. Backed by Sequoia Capital, Ribbit, Conviction, Evantic, AI Grant, and Pear VC. Notable context includes Sequoia partner Bryan Schreier as an early investor in Qualtrics. Salary range: The base range for this role is $150,000 – $300,000. Actual compensation depends on skill set, experience, and location. If this range doesn\'t match your expectations, we still encourage you to apply. Benefits that support you: Comprehensive healthcare and dental coverage, flexible time off, and an environment that values balance and trust. Growth opportunities: As an early member of the team, you will shape processes from scratch and grow alongside the company. #J-18808-Ljbffr