Senior Staff Product Manager, AI Platform

ServiceNow•Santa Clara, CA

3d•$190,900 - $334,100•Hybrid

About The Position

The AI Platform team owns the foundational inference layer that every AI experience on the Now Platform depends on. This includes how models are served, routed, and optimized across regions and deployment environments, such as data centers, hyperscalers, and regulated segments. The team is responsible for ServiceNow's multi-model strategy and unit economics, and drives the AI model strategy and transitions that underpin the platform's cost, performance, and flexibility at enterprise scale. This role focuses on scaling AI deployment and customer success across every ServiceNow AI implementation, within a growing team. This is a unique opportunity for an agentic AI product leader to have full end-to-end ownership of the inference layer powering AI across an enterprise platform used by thousands of customers. The role involves managing the infrastructure, economics, and vendor strategy behind all AI models, operating at the intersection of technology and business strategy. You will shape the selection, integration, and optimization of open-source and third-party models for cost efficiency in complex, regulated environments. ServiceNow's cross-vendor, multi-model approach and its position as a top enterprise AI adopter provide a vantage point to influence the evolving AI inference landscape company-wide.

Requirements

10+ years of product management experience
Recent hands-on experience shipping agentic products.
Deep technical fluency in inference technology: model serving, GPU economics, and latency/throughput trade-offs.
Solid understanding of data sovereignty requirements and how they shape deployment decisions across regulated markets.
A track record of vendor partnerships and build-vs-buy decision-making at scale.
Demonstrated ability to operate independently on ambiguous, company-level problems.
Proven skill influencing senior stakeholders without formal authority.
Comfort working cross-vendor across a multi-model, multi-hyperscaler environment.

Nice To Haves

Prior experience partnering directly with hyperscaler platforms on AI infrastructure strategy.
Experience shipping AI products or platforms into regulated or highly compliance-sensitive customer environments.

Responsibilities

Strategy and roadmap for the AI inference layer end-to-end, across every region and deployment environment ServiceNow operates in.
Third-party and open-source model availability, selection, and integration — including performance, latency, and integration agility trade-offs.
Inference economics: shaping cost-per-token and unit economics as usage volume scales.
Vendor and partnership decisions behind the model layer, including build-vs-buy calls and hyperscaler relationships.
Model strategy and transitions across data center, hyperscaler, and regulated-environment deployments, including data sovereignty requirements.
Cross-functional execution alongside the existing AI Platform product team as the group scales to meet growing enterprise demand.