Principal Software Engineer

ServiceNow•Santa Clara, CA

About The Position

The engineering organization is a dynamic group of builders, thinkers, and problem-solvers focused on delivering scalable, AI-powered software products that improve how organizations work. We value clean architecture, intuitive experiences, operational excellence, and a culture of continuous improvement. Every engineer plays an important role in shaping the quality, reliability, and long-term success of our products. The Service Operations Business Unit brings together IT Service Management (ITSM), IT Operations Management (ITOM), and CMDB capabilities on the ServiceNow Platform. This product engineering organization builds the software that helps customers deliver resilient, intelligent, and efficient enterprise services. The Service Operations product portfolio connects incident, request, fulfillment, infrastructure visibility, service mapping, trusted configuration data, automation, and AIOps into a unified operating model. By combining service delivery with operational intelligence and trusted operational context, these products help customers move toward proactive, AI-assisted, and increasingly self-healing operations at enterprise scale. Together, these capabilities help customers modernize how they deliver and operate services, improve reliability, reduce manual effort, and drive measurable productivity outcomes on a single platform. As a Principal Software Engineer, you will architect and build assistive and autonomous AI-native products to usher customers (IT departments using our IT service and operation management applications) into an agentic-first era. The work will span large-scale distributed systems, data ingestion, context creation and utilization, agentic harnesses, cost optimization, agentic feedback loops to ensure value realization for our customers. This role requires thought leadership, deep technical expertise, strong architectural judgment, and a keen understanding of the scientific method to ship and refine real product through iterative experimentation.

Requirements

15+ years of related engineering experience, or equivalent practical experience.
Strong experience building and operating large-scale distributed systems, enterprise platforms, workflow systems, data-intensive products, integration frameworks, or cloud-scale infrastructure.
Deep understanding of system design for scale, reliability, observability, fault tolerance, data quality, security, and production readiness.
Strong technical depth in Java, Python, or similar programming languages.
Proven ability to define technical direction, influence architecture across teams, and translate ambiguous product strategy into executable engineering plans.
Ability to operate as a Principal IC by leading through technical credibility, collaboration, and influence rather than formal authority.
Strong judgment in balancing long-term architecture with pragmatic execution, customer impact, engineering velocity, and business priorities.
Experience mentoring senior engineers, raising engineering standards, and building reusable patterns that create leverage across teams.
Ability to reason about AI-assisted enterprise workflows, including data quality, workflow correctness, evaluation, observability, safety controls, and human-in-the-loop review.

Nice To Haves

Experience with AI-powered products, automation platforms, AI-assisted workflows, or agentic systems is strongly preferred.
Experience with enterprise service management, IT operations, CMDB, discovery, service mapping, AIOps, observability, workflow automation, endpoint management, or operational intelligence is a strong plus.
Experience working with large-scale enterprise customers, production systems, and complex migration or modernization efforts is a plus.

Responsibilities

Lead architecture and technical strategy for assigned problem areas within ITSM/ITOM products, working with product and engineering leaders to understand blockers and opportunities around AI-native evolution and value realization.
Contribute hands-on to spiking and shipping solutions. Validate architectural hypotheses through code, not theory. Build prototypes, reference implementations, and critical path components to prove feasibility and guide teams.
Design and validate solutions through evidence-based spiking: formulate hypotheses, run experiments, measure outcomes, and use data to guide architectural decisions and product direction.
Architect the evolution of current solutions toward AI-native capabilities—identifying where agentic patterns, data utilization, or autonomous workflows can unlock customer value. Translate architectural recommendations into executable work.
Identify and address value realization gaps in agentic products that exist but aren't delivering expected outcomes. Work with teams to diagnose root causes (architecture, UX, data quality, feedback loops, cost) and recommend targeted improvements.
Establish architecture patterns and best practices specific to your problem domain. Document tradeoffs, rationale, and implementation guidance to help teams move faster and make consistent decisions.
Guide teams through complex technical decisions and design reviews. Challenge assumptions with data, surface architectural risks early, and help teams navigate tradeoffs between shipping speed and long-term durability.
Collaborate across ITSM/ITOM engineering teams to share learnings, validate approaches, and accelerate adoption of patterns that work.