Senior Inbound Product Manager, CRM Voice AI

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.

About the Team:   

CRM Voice AI builds autonomous voice agents for customer service that resolve customer interactions end-to-end and drive significant value for the business. We're a team inside ServiceNow's CRM business unit, shipping production voice AI with enterprise customers today and scaling aggressively. Our agents run on a real-time streaming pipeline with best-in-class orchestration, integrated into the same platform where many of our customers already manage their front, middle, and back-office workflows. For those that don't, the voice agent is often the tip of the spear that brings them in. We compete directly against well-funded AI startups and CCaaS incumbents, and we're winning. 

How We Work:   

We work in pods - small, dedicated teams embedded with a single enterprise customer, building their voice agents from first call to self-sufficiency. A pod owns the full lifecycle: agent shadowing, conversation design, build, production go-live, monitoring and optimization and the handoff that makes the customer self-sufficient so the pod can move on to the next one. Each pod pairs forward-deployed engineers with a product manager who owns both the customer outcome and the product learning that comes from it. 

Every PM on this team runs at least one pod directly and has visibility across others. You're in the customer's world - on their calls, in their systems, solving their problems - while simultaneously shaping what the product becomes. The learnings from your pods feed directly into the platform roadmap and into repeatable, productized assets that scale beyond any single customer. 

What This Role Owns:   

You run two pods closely - hands-on through the full build lifecycle with two enterprise customers simultaneously, from agent shadowing through production go-live.  You own the relationship with each customer’s team – setting the timelines and expectations, then delivering on them.  You'll become one of the most experienced people in the company at knowing what it actually takes to ship a voice agent that works in the real world. 

For those pods, you and your team of FDEs own agent design, the build and evaluation. 

Your second area of focus is the tooling and intelligence layer that makes voice agents better and easier to build. This spans automated evaluation frameworks (how do we systematically measure whether a voice agent is good?), analytics (what happened on that call and why?), admin experience (how does a customer manage and improve their own agents?), and smarter agentic design patterns like deterministic procedures that give agents reliable behavior on structured tasks. You're building the infrastructure that lets this team, and eventually our customers, move faster and build better agents. 

Why This and Not Somewhere Else:   

This role puts you directly in front of enterprise customers running production voice AI from day one. You're not waiting to earn customer exposure - it's the job. The pod model means you'll accumulate more production voice AI experience in a year than most PMs get in several, across different industries, different contact center environments, and different conversation types. At the same time, the evaluation frameworks and agentic design patterns you build have reach well beyond your own pods. This team has a direct seat at the platform table, so the tooling you create shapes how ServiceNow thinks about voice agent quality at scale. 

What You Bring:

Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry.  

5+ years of product management experience, or equivalent experience in a technical role such as engineering, solutions consulting, or technical program management where you owned product outcomes. 

Hands-on experience building and evaluating AI agents or conversational AI systems - conversation design, prompt engineering, testing and iteration against real user interactions. 

Comfort with data and evaluation. You think naturally about how to measure whether something is working and how to build systems that do it at scale. 

Experience working directly with customers or end users on technical products. You don't need enterprise sales experience, but you need to have been in the room where the work happens. 

Strong technical foundation. You can read code, understand API contracts, and hold your own with engineers on system design. 

An instinct for repeatable process. You see a problem solved once and immediately think about how to solve it for every customer. 

Experience with conversational AI, voice technology, or contact center operations. 

Even Better:   

Familiarity with agentic AI design patterns and how to give an AI agent reliable, structured behavior alongside open-ended reasoning.