Staff Inbound Product Manager, AI Specialists and Voice AI

Staff Inbound Product Manager, AI Specialists and Voice AI Full-time Employee Type: Regular Region: AMS - North America and Canada Work Persona: Flexible or Remote Company Description It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started. Join us to put AI to work for people.

Zero Touch Support exists to make working with your IT department easy and pain-free. That is a bigger surface than any one product. It starts at the front door, where Moveworks, Employee Slate, and our chat experiences meet employees inside the tools they already use and resolve most of what they need before a ticket ever exists. When something does need real work, our AI Specialists pick it up, carry it end to end, and close it. Voice AI does the same for the people who would still rather pick up the phone. Employee Insights shows us and our customers where the friction actually sits, so the whole system improves on a loop instead of on a release cycle. Put together, that is the difference between an employee filing a ticket and waiting, and an employee just getting on with their day.

You will own a piece of that portfolio outright. What it does, who it is for, what “good” means, and whether we are honestly there yet. The interesting part of this job is not the model. It is everything around the model. Every customer environment is different: different knowledge quality, different catalog, different naming conventions, different appetite for letting an agent act on its own. An agent that performs great on a clean eval set can behave differently in a live enterprise for reasons that have nothing to do with reasoning ability. Understanding why, and designing for it, is the job. We treat evaluation as a product surface rather than a QA step. We run production-ready code against real customer data before we ship, we write and tune our own judge prompts, and eval results are our launch criteria. ServiceNow moves faster than a company our size has any right to. We shipped an autonomous L1 specialist, and the evaluation discipline behind it, in the time most enterprises spend forming a committee. We are not reacting to AI. We are deciding what AI-first, enterprise-grade software actually means, for the largest companies in the world, who run their business on our platform and cannot afford for us to get this wrong. A lot of that definition does not exist yet, which means on many weeks you will be the person framing the problem rather than receiving it. How we work is changing as fast as what we build. We are AI-native in our own process, not just in what we ship: prototype with AI instead of describing the idea, put a working demo in front of people instead of a slide about a demo, generate the deck, draft the spec, stand up a rough eval harness. ServiceNow invests in state-of-the-art tooling and expects you to use it, so the role itself is being redefined in real time, and product managers are better positioned than anyone to lead that shift and pull an AI-product team forward with them. We prove products out in the wild before we scale them. That means working forward deployed: embedded with a customer, in their environment, building and tuning against their real data and their real edge cases until the it works. Then the harder half, turning what you learned into something that generalizes to the next thousand customers. At most AI companies those are two different