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San Francisco, California, United States
Onsite
TL;DR: We're hiring engineers who can build a complex AI-native product on a small team of former founders and top-tier builders.
Applications for this position will be accepted on an ongoing basis.
As AI gets better at building things, the bottleneck shifts to knowing what to build. We're the bridge between AI systems and what humans actually want. Today our customers are companies. Soon, AIs themselves will be our customers.
Our platform runs AI-moderated video interviews at massive scale. We find the right people from a network of millions, our AI conducts open-ended conversations with thousands of them in parallel, and we surface what to build next. What used to take research teams weeks per study, we do in hours.
Where it's going: every interview feeds a human preference model. We simulate human behavior at scale: how people react to new ideas, how they make decisions, how preferences shape markets, and how change ripples through society. We expose this as the Human API. An AI agent writes code, asks Listen whether users would actually want a feature, gets a grounded answer back, and iterates. Closed-loop product development at AI speed. Every coding agent will eventually need this signal.
Listen was acquired by Salesforce in 2026 and is being incubated within Salesforce AI Labs!
Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce
World-Class Team: Founded by serial entrepreneurs — Alfred (Bemlo, YC W22) and Florian (IOI medalist, ICPC World Finalist) — and built with talent from Google, Meta, Tesla, Amazon, Jane Street, and X, alongside Bain, Goldman Sachs, McKinsey, and Sequoia-backed startups like Applied Intuition, Scale AI, and Rippling. Over 30% of our team are former founders, and multiple are competitive programming medalists.
Hypergrowth: Since launching, Listen has grown annualized revenue 15x and completed over 2 million interviews — backed by $100M in total funding led by Ribbit Capital, with Sequoia, Conviction, and Pear VC participating.
Traction: Already serving 15% of Fortune 100s. Enterprise wins and expansions across Anthropic, Microsoft, Nestlé, Perplexity, Sweetgreen, and more — with teams telling us research that used to take six to eight weeks now happens in days.
Database of Humanity. Listen maintains a database of millions of people. We match profiles based on voice, face, and device IDs. Those profiles let us see how opinions change over time, prevent fraud, and find any niche audience.
Emotional Intelligence. There's a gap between what people say and what they think. Our AI interviewer reads tone, hesitation, and facial micro-expressions to go beyond the transcript. We've shipped the first version. We're working on surpassing even the best humans.
Preference Model. Updating the preference model is a research problem: what we already know, when to refresh it, which questions give the highest signal, and how to quantify the uncertainty in our predictions.
Human API. A model of millions of humans is only useful if you can call it from where decisions happen. We want to embed this into Slack, Linear, IDEs, and coding agents themselves. Imagine an agent shipping code, asking Listen what humans actually want, taking action, and iterating.
Agent Evals. Every part of our product is built AI-first. Study Composer helps customers scope and design studies. Research Agent analyzes thousands of responses and writes the report. The ceiling is what McKinsey does for $1M per engagement. The bottleneck is evaluating those qualitative outputs. Once you have the eval, you can hill-climb.
You solve problems end to end. The team is split vertically, so every engineer owns a part of the product and makes decisions across the LLM pipeline, infrastructure, backend, and UX.
You're a future or past founder. You scope your own work, think about the customers, and own your decisions.
You care about getting things right. Moving fast is essential, but a 100% solution is much more powerful than an 80% one. When something breaks, you go to root cause.
You're excited about pushing LLMs to their limits. We work directly with the frontier model labs on new releases and constantly probe where they break.
You communicate complex ideas in writing. We work independently with one meeting a week, so writing is how tradeoffs, problems, and decisions get worked through together.
You're highly technical. Most of our team started coding as teenagers and nerd out on details from language design to compilers.
When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.
Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that's inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications - without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.
At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is $180,000-$300,000 annually.
Your recruiter can share more about the specific salary range for the job location during the hiring process. The rangce represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable
