Define and drive the architectural and engineering direction of the ServiceNow platform.
Ensure platform initiatives are delivered securely, at scale, and in alignment with enterprise standards.
Lead technical feasibility and integration efforts as governance expands to include Artificial Intelligence
Solution Domains Across IT, HR, Risk and Platform.
Establish and evolve platform standards, patterns, and guardrails.
Ensure governance models are scalable, pragmatic, and consistently applied across the ServiceNow ecosystem.
Provide technical leadership for GenAI capabilities on ServiceNow, business case development, architectural alignment with enterprise AI strategy.
Collaborate to enforce consistent UX and interaction patterns across employee-facing experiences.
Partner with Platform Architects to identify technical debt across GenAI and platform domains, drive modernization efforts that align with enterprise architecture standards.
Serve as a technical authority and integrator across governance, GenAI capabilities, platform stability, and modernization initiatives.
Requirements
7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education.
5+ years of ServiceNow Development, Design, or Implementation experience
Proven experience establishing and scaling a Platform Center of Excellence (CoE) with enforceable governance models that balance innovation with platform health and technical debt control.
Hands-on expertise designing and operationalizing AI governance frameworks on ServiceNow, including AI Search, Now Assist, Virtual Agents, and Agentic flows, with emphasis on security, data residency, model risk management, prompt/response guardrails, and performance.
Advanced experience architecting resilient, scalable, maintainable integrations (APIs, eventing, messaging) across large tool ecosystems; familiarity with A2A protocols, zero-trust patterns, and observability/SRE practices for integration health.
Experience in financial services or other regulated industries; familiarity with model risk management and data protection in AI-enabled features.
Executive presence and influence—serving as a trusted partner to engineering leadership, product management, enterprise architecture, and technology executives; skilled at portfolio rationalization, platform strategy alignment to product strategy, and value realization.