Principal Software Engineer – UI

Short Summary

Principal Software Engineer – UI with ServiceNow. What you get to do in this role: Platform Architecture & Strategy — Define and own the long-term architecture of a server-rendered web component platform that powers AI-native user experiences across the product. You'll make the key decisions on rendering, component runtime, design systems, and streaming UX for AI-generated content, and keep the experience layer resilient…

Key Details

• Position / opportunity: Principal Software Engineer – UI
• Organization: ServiceNow
• Country / coverage: India
• Location: Hyderabad, , India
• Work arrangement: On-site
• Opportunity type: Jobs
• Sector: Information Technology
• Compensation: Not specified
• Duration: Not specified
• Start date: 2026-09-29
• Application deadline: Not specified

Description

What you get to do in this role: Platform Architecture & Strategy — Define and own the long-term architecture of a server-rendered web component platform that powers AI-native user experiences across the product. You'll make the key decisions on rendering, component runtime, design systems, and streaming UX for AI-generated content, and keep the experience layer resilient and coherent as the platform scales. Rendering & Performance — Own end-to-end experience performance: server-side rendering, streaming HTML, hydration correctness, and time-to-interactive. Push the state of the art in server rendering of web components so experiences are fast, deterministic, and consistent between server and client. AI-Native Intelligent Experiences — Build the platform primitives product teams use to expose agentic backends to end users, including recommendations, autonomous triage, generated insights, and multi-step agent reasoning. Own the hard UX problems specific to AI-native products: streaming model output, progressive disclosure of agent reasoning, graceful handling of latency and uncertainty, and human-in-the-loop review flows that make autonomous behavior legible and controllable. Secure, Scalable Runtime — Design how the platform runs in production on Kubernetes: sandboxed execution of application code, multi-tenant isolation, secure credential and token propagation, memory and resource budgeting, version-tiered rollouts, and observability for a large Node.js fleet under real traffic. Developer Platform & Ecosystem — Shape the component model, data-loading and context APIs, design system, tooling, and guardrails that let many teams build applications on the platform. Make the right path the easy path. Agentic Pipeline Awareness — Work closely with ML and platform teams building agent orchestration and tool-calling infrastructure (multi-agent dispatch, MCP-style tool integration, reasoning traceability). Translate what those backends can do into UX patterns that are usable, safe, and trustworthy. Business Alignment — Tie platform and experience architecture to business goals, so that engineering velocity, experience quality, and adoption of AI-native features support customer acquisition, retention, and time-to-market. Hands-on Engineering — Write high-performance, production-grade code across the experience stack (TypeScript, Lit.js / Web Components, Node.js, modern build tooling) and the runtime stack (Kubernetes, containerized services). Debug the hardest problems yourself, from hydration mismatches to memory leaks to intermittent production failures. Cross-functional Execution — Drive business-critical platform outcomes together with ML, backend platform, SRE, security, UX, and product teams. Engineering Culture — Mentor senior and staff engineers, lead architecture reviews, raise the bar on testing and reliability, and build a culture of rapid, impact-driven innovation. Ownership & Initiative — Spot platform and experience gaps before they become problems, propose solutions, align stakeholders, and own execution. To be successful in this role you have: 15+ years of software engineering experience, focused in frontend or web platform engineering at a high-growth tech company or top-tier AI lab. Deep expertise in web platform internals: Web Components and Shadow DOM, server-side rendering and hydration, streaming, module loading, and browser performance. Production experience with Lit.js, React, or comparable frameworks, and a clear view of the tradeoffs between them. Strong server-side JavaScript/TypeScript engineering skills: Node.js, HTTP/2, proxies and streaming, V8 memory behavior, and isolate or worker-based execution models. Hands-on experience running latency-sensitive services on Kubernetes, including resource management, rollout strategies, Helm, and production observability. Strong web security fundamentals: session and token handling, egress control, sandboxing of untrusted code, and trust boundaries in multi-tenant systems. Has shipped intelligent, AI-driven user experiences (not just consumed an LLM API), with strong intuition for how agent and model output should surface to real users. Hands-on experience…

Responsibilities

• What you get to do in this role: Platform Architecture & Strategy — Define and own the long-term architecture of a server-rendered web component platform that powers AI-native user experiences across the product.
• You'll make the key decisions on rendering, component runtime, design systems, and streaming UX for AI-generated content, and keep the experience layer resilient and coherent as the platform scales.
• Rendering & Performance — Own end-to-end experience performance: server-side rendering, streaming HTML, hydration correctness, and time-to-interactive.
• Push the state of the art in server rendering of web components so experiences are fast, deterministic, and consistent between server and client.
• AI-Native Intelligent Experiences — Build the platform primitives product teams use to expose agentic backends to end users, including recommendations, autonomous triage, generated insights, and multi-step agent reasoning.
• Own the hard UX problems specific to AI-native products: streaming model output, progressive disclosure of agent reasoning, graceful handling of latency and uncertainty, and human-in-the-loop review flows that make autonomous behavior legible and controllable.

Requirements / Eligibility

• modern build tooling) and the runtime stack (Kubernetes, containerized services).
• Debug the hardest problems yourself, from hydration mismatches to memory leaks to intermittent production failures.
• Cross-functional Execution — Drive business-critical platform outcomes together with ML, backend platform, SRE, security, UX, and product teams.
• Engineering Culture — Mentor senior and staff engineers, lead architecture reviews, raise the bar on testing and reliability, and build a culture of rapid, impact-driven innovation.

How To Apply

Use the Apply now button and follow the instructions on the application page.