Principal Software Engineer - AI Native UX

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.

What you'll do

UX Architecture & Strategy — Define and own the long-term architecture for AI-native user experiences across the platform, making critical build-vs-buy decisions (design systems, agent-to-UI interaction patterns, real-time/streaming UX for AI-generated content) to ensure the experience layer stays resilient and coherent as the platform scales.

AI-Native Intelligent Experiences — Design and build user-facing surfaces where agentic backends - recommendations, autonomous triage, generated fixes/insights, multi-step agent reasoning - are exposed to end users through fast, trustworthy, low-friction interaction patterns. Own the hard UX problems unique to AI-native products: progressive disclosure of agent reasoning, graceful handling of uncertainty/latency, human-in-the-loop review flows, and making autonomous system behavior legible and controllable to end users rather than a black box.

UXC & Workspace Platform — Deep ownership of the UXC (User Experience/Workspace, UI16) surface — component architecture, design system consistency, and performance — as the primary canvas AI-native features are built on top of.

Agentic Pipeline Awareness — Partner closely with platform/ML teams building the agent orchestration and tool-calling infrastructure underneath (multi-agent dispatch, MCP-style tool integration, reasoning traceability) — translating what these backends can do into UX patterns that make them usable, safe, and trustworthy for real users.

Business Alignment — Align UX and technical architecture with business goals, ensuring engineering velocity, experience quality, and adoption of AI-native features directly support customer acquisition, retention, and time-to-market.

Hands-on Engineering — Write high-performance, clean, production-grade code primarily across the frontend/experience stack (Lit.js, React/TypeScript, design systems, component architecture), with working fluency in backend/platform code (Java, Python, Postgres, K8s) to collaborate effectively with platform teams.

Cross-functional Execution — Drive business-critical UX and platform outcomes in close collaboration with ML, backend platform, and product teams.

Engineering Culture — Mentor senior engineers, champion UX and engineering excellence, and foster a culture of rapid, impact-driven innovation in AI-native product development.

Ownership & Initiative — Proactively identify UX and platform gaps in the AI-native experience, propose solutions, align stakeholders, and drive execution with a high degree of ownership.

Requirements

Experience leveraging or critically thinking about how to integrate AI into engineering and platform work—AI-powered tooling, automated operational workflows, agentic systems for fleet visibility and operations, or reasoning about AI’s impact on how infrastructure is built and run.; 15+ years of software engineering experience with demonstrated progression into senior technical leadership, and a track record concentrated in user experience and frontend platform engineering .; Deep UXC / AI-native UX expertise - has shipped intelligent, AI-driven user experiences (not just consumed an LLM API), with strong intuition for how agent/model output should surface to real users.; Hands-on experience with agentic/multi-agent systems from the consumer side — understands agent orchestration, tool-calling protocols (MCP or equivalent), and reasoning traceability well enough to design UX around them, even if platform-layer implementation sits with another team.; Strong hands-on coding ability with deep design thinking in the frontend/experience stack (React/TypeScript, component/design systems), working proficiency in backend fundamentals (K8s, Java, Python, Postgres) to bridge into platform architecture conversations.; Demonstrated ability to connect UX and engineering decisions to business outcomes - adoption, retention, time-to-market, not just technical metrics.; Self-driven with strong ownership, able to identify UX and system gaps, propose solutions, align stakeholders, and execute at startup pace.; Experience integrating or critically evaluating AI tools/agentic workflows in product and engineering decision-making, particularly from a user-experience and trust/legibility angle.

Nice to have

Prior experience in distributed systems performance/scalability, even if not the primary focus of recent roles.; Open-source contributions to major AI-native UX, design-system, or agent-framework projects.; Prior startup experience working closely with Product and Growth teams in an early-stage environment.