Principal Inbound Product Manager

ServiceNow•Santa Clara, CA

1d•$221,200 - $387,100•Hybrid

About The Position

ServiceNow is looking for a Principal Inbound Product Manager to build the evaluation and feedback backbone that makes our AI-powered support products trustworthy, measurable, and continuously improving. We are investing in building structured mechanism for statistical sampling, human review, or feedback capture that closes the loop back into the product. This role owns enabling that mechanism from the ground up, and applying it consistently across all AI-enabled products in the portfolio. This is an inbound-facing role: your primary customers are the product teams and Customer Support teams across the organization, and your core deliverable is the evaluation & governance infrastructure, taxonomy, and process that lets every AI feature get measurably better over time.

Requirements

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.
15+ years of product management , with recent hands-on experience building AI Agents, AI evaluation, feedback, or quality frameworks for AI/ML-powered products.
Strong AI product sense, able to reason about measuring AI application performance, failure modes, and quality tradeoffs, not just feature delivery.
Experience designing structured feedback or evaluation systems: golden datasets, statistical sampling, human-in-the-loop review, or similar.
Data-driven decision-making, comfortable defining metrics, interpreting telemetry, and using both to prioritize.
Proven track record leading cross-functional initiatives without direct authority, across Product, Engineering, Data Science, and Operations.
Excellent stakeholder management and communication skills; able to influence senior leaders and align multiple teams around a shared framework.

Nice To Haves

Experience in a customer support, service delivery, or similarly operational environment is a plus.

Responsibilities

End-to-end design of the AI product evaluation ecosystem: automated evals, human-in-the-loop review, and a structured feedback taxonomy applied consistently across the organization's AI-enabled support capabilities.
A closed-loop process that converts feedback and review findings into concrete product and model improvements.
Cross-functional coordination across Product, AI/ML Engineering, Data & Telemetry, and AI Operations to unify how feedback is captured, reviewed, and actioned.
The requirements and prioritization inputs that drive continuous improvement in resolution quality and effectiveness, benefiting both internal support teams and external customers.