USD per year
Senior Product Manager, Platform (AI)
$170K - $190K•US / Remote (US) Job type Full-time Role Product Experience 3+ years Visa US citizen/visa only Apply to Vouch and hundreds of other fast-growing YC startups with a single profile. Apply to role ›
About the role
About Vouch: Vouch is the insurance broker that powers ambition. We’re a tech-enabled insurance advisory and brokerage purpose-built for growing companies in technology, life sciences, and professional services. Our clients are ambitious leaders building complex businesses, and we help them manage risk with tailored advice, smart coverage, and responsive service. Backed by over $200M from world-class investors, Vouch combines deep industry expertise with AI-powered tools to deliver a better insurance experience. Our digital workflows reduce friction, speed up decisions, and give our clients the confidence to move faster. Why should you join our team and Vouch? Not only is this an exciting and growing team where you can drive a real impact on our operational scalability, but Vouch is also the preferred insurance provider to customers of Y Combinator, Brex, Carta, and WeWork. We’re a quickly growing startup that believes in transparency and acknowledgment with our team members and cultivating a values-driven company. Our values are "Be Client Obsessed", "Own it together", "Act with integrity and empathy", "Stay Curious and Grow", and "Empower People." What does a work environment look like at Vouch? Vouch has employees located across the U.S., with offices in San Francisco, Chicago, and New York City. This role can be based anywhere in the U.S. as long as you can work our Vouch core collaboration hours (8:30 am-2:30 pm Pacific Time) when most internal meetings are held. About the role We're building an AI system that learns from how domain experts make decisions — and gets measurably better over time. The challenge isn't building another chatbot or copilot. It's designing a system that can extract structured intelligence from messy, real-world professional workflows, identify reliable patterns across many decisions, and surface that knowledge to the point where it's actually useful — without requiring anyone to change how they work. The PM is responsible for designing the loops that capture judgement, play back recommendations and advice to brokers, and holds the team accountable to a standard of truth over confirmation. About the team This is a founding role on a small pod focused on a narrow problem space with a large solution space. We're selecting for ambiguity tolerance, iteration speed, and range over process discipline. The tradeoff is explicit: we accept messiness in exchange for faster learning. The PM works embedded in a team of AI and software engineers. You'll report to the Director of Product and interface regularly with the leadership team as the voice of the pod — communicating progress, surfacing blockers, and translating system performance into strategic implications. What this means for you You'll own the problem and success definition — not the feature list. This role requires a high-ownership mindset: you don't just prioritize what's asked — you define the workflow, what use case and workflow makes the most sense to prioritize to prove out the system, and what the system needs to prove at every stage to answer “is this actually working” This is not a traditional PM role. There are no customers in the conventional sense. There's a thesis, a set of domain experts who are your ground truth, and an AI system that either outperforms a generic model or doesn't. You own the bar. What you'll do
Design the judgment capture system
- Define what broker judgment looks like when it's captured correctly — the artifact schema that turns unstructured decisions into structured intelligence.
- Design the feedback loops that allow domain experts to validate, correct, and enrich what the system surfaces — without adding friction to how they already work.
- Own the broker relationship: understand what advice actually looks like, what experts trust, and what the system gets wrong in interesting ways.
- Map workflows into tangible assets, advice units, and recommendations for brokers to act on.
- Translate expert corrections into system improvements. When brokers tell you the output is wrong, that's your most valuable signal — make sure the team acts on it.
Define and hold the standard for "good"
- Own the evaluation framework: what does it mean for this system to be materially better than a generic AI model with the same context?
- Define success criteria for each phase — not in business metrics, but in system performance. Does the extraction work? Do brokers trust the patterns? Is month 8 better than month 5?
- Build instrumentation with the engineering team to track whether the system's intelligence is actually improving. If it isn't, the answer is stop — and you should find that useful, not threatening.
- Distinguish real learning from noise. Patterns that don't hold are not product failures — they're data. Own how the team uses them.
Drive priorities and protect velocity
- Translate domain complexity into a prioritization framework the team can execute against — without perfectly defined requirements.
- Work with GTM and embedded domain experts to ensure the team is solving the right problem. You are the interface between what brokers need and what the system can produce.
- Remove ambiguity without adding process. This team moves fast — your job is to create clarity, not overhead.
About you
Required
- 3–5 years of product experience,...