Associate Forward Deployed Product Manager

About Fractional AI

How do you turn a decades-old dataset into an industry-leading medical coding agent? Teach an AI receptionist to book appointments in Spanish? Automatically generate working data connectors from API docs? Build agents that write, test, and deploy their own software packages?

Fractional AI is a startup in the heart of Silicon Valley targeting the biggest greenfield opportunity in the economy: transforming companies with AI software at a scale the market is only beginning to understand. Our clients include Zapier, Airbyte, and companies from industries ranging from data infrastructure to healthcare and life sciences.

We were founded by repeat founders Chris Taylor, Eddie Siegel, and Travis May (Founder of Datavant, $7B exit), and are backed by Shaper Capital. Most of our engineers are former founders or staff engineers from top tech companies like Google and Stripe.

We're headquartered in SF with offices in NYC, Raleigh-Durham, and Dubai.

Our customers come to us with ambitious, often fuzzy goals — make content moderation faster, customer service cheaper and better, unlock new integrations, automate the workflows no one else can touch.

Your job is to help turn those goals into AI-powered solutions that work in the real world. You'll work closely with experienced team members while ramping to own parts of projects end-to-end. Ownership scales with performance: you'll take on more responsibility, including running projects, as soon as you demonstrate you're ready. You'll be expected to grow into independently running projects within 12–24 months.

This is a forward-deployed, full-stack customer role:

• Part engagement manager — you build trust quickly and own day-to-day with the client.

• Part product manager — you help drive what we build and why.

• Part delivery/program manager — you run the execution motion.

• Part operator — you jump into the gaps to keep things moving without waiting to be asked.

You’ll work on small engineering pods (2–5 engineers and a senior PM), shipping multiple AI products every year.

You’ll take ownership of execution and delivery operations while building toward full ownership of end-to-end projects.

• Own the customer relationship. Build strong day-to-day relationships with customers and grow into a trusted partner. Join early-stage calls, run discovery, synthesize feedback, and set clear expectations across all levels of the organization.

• Shape what we build and why. Contribute to defining product builds, refining scope, and identifying high-leverage use cases. Translate ambiguous business problems into crisp problem statements, user journeys, and success metrics.

• Turn messy problems into shipped solutions. Translate ambiguous needs into clear requirements, PRDs, and plans for engineers. Shape workflows, edge cases, and evaluation criteria for AI-powered systems.

• Drive execution across multiple AI products. Increase team leverage by owning delivery mechanics — tracking progress, coordinating stakeholders, running the day-to-day rhythm, and proactively flagging risks with clear recommendations.

• Help create demand, not just fulfill it. Jump on early, messy conversations where the project is still a vague idea. Help founders and sales tease out real pain, sketch solution approaches live, and spot expansion opportunities.

• Drive adoption and long-term impact. Work with client teams on rollout, enablement, and change management so the systems you build actually get used. Bring back insights that inform Fractional's playbooks and product direction.

• Bring judgment and clarity. When requirements are fuzzy or customers change course, help drive toward the highest-impact solution and be the person in the room who can say: here's what we're trying to do, here's what we know, here's the plan.

• Customer-facing experience under pressure. You've taken meaningful ownership in projects where customers were stressed, stakeholders weren't aligned, and the path wasn't obvious. You're comfortable pushing back, reframing problems, and holding the line on quality. We typically look for 1–3 years in product, consulting, or implementations, although we care more…