Principal Software Engineer

ServiceNow•Santa Clara, CA

2d•$221,200 - $387,100•Hybrid

About The Position

The Security and Risk Engineering organization is a dynamic group of builders, thinkers, and problem-solvers dedicated to delivering scalable, world-class AI-powered security solutions to reduce risk and protect the company and our customers. We value AI first solutions, clean architecture, intuitive user experiences, and a culture of continuous improvement. Security is a key strategic growth area for ServiceNow, and every engineer here plays a key role in driving innovation and shaping the quality and reliability of our security and risk products.

Requirements

Deep technical expertise in modern AI/ML, with demonstrated experience building production AI systems using LLMs, foundation models, agentic architectures, RAG, embeddings, knowledge retrieval, model evaluation, and related technologies.
Strong understanding of agentic architectures, including planning and reasoning, tool use, context and memory, multi-agent systems, evaluation, observability, guardrails, and human-in-the-loop patterns.
Strong technical foundation in software architecture, distributed systems, cloud-native platforms, data systems, and APIs, with the ability to go deep into architecture and code.
Experience designing and building highly performant and scalable distributed systems.
Strong proficiency in Python and experience with modern AI frameworks and infrastructure; experience with Java, Go, or similar languages is valuable.
An innovator's mindset with the ability to challenge conventional approaches, identify opportunities created by rapidly evolving AI technology, and turn ambitious ideas into working products.
Ability to operate effectively in ambiguity and balance rapid experimentation with the rigor required for enterprise-grade security products.
Strong product instincts and the ability to connect technology innovation to customer problems, differentiated experiences, and business outcomes.
Executive-level communication skills and the ability to articulate a compelling technical vision to engineers, customers, and senior leadership.
15+ years of software engineering experience, including significant technical and engineering leadership responsibility.
Demonstrated experience designing and delivering AI/ML-powered products and platforms in production.
Strong backend engineering experience with distributed systems, APIs, microservices, and cloud-native architectures.
Demonstrated ability to design systems that scale to enterprise workloads.
Hands-on experience with modern AI development technologies, including frontier LLMs, agent frameworks, retrieval/vector technologies, model evaluation and observability.
Extensive experience using AI-native development tools and coding agents such as Claude Code, Codex, Cursor, Windsurf, or equivalent as part of the software development lifecycle.
Experience leading technical initiatives spanning multiple teams without direct authority.
Experience with cloud platforms in Kuberneties is a must and modern DevOps practices.
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline, or equivalent practical experience.

Nice To Haves

Experience with cybersecurity problems such as threat detection, vulnerability and exposure management, security operations, identity security, investigation, risk prioritization, or autonomous remediation strongly preferred.
Experience in cybersecurity products or deep familiarity with modern security architectures and security operations is strongly preferred.

Responsibilities

Define the technical vision and architecture for AI-native security solutions, leveraging frontier models, agentic AI, reasoning, retrieval, knowledge systems, and advanced ML techniques.
Explore and apply emerging AI capabilities to solve complex cybersecurity problems in fundamentally new ways—not simply augment existing products with AI.
Define technical architecture and engineering standards that improve scalability, reliability, performance, and maintainability.
Partner closely with Product, UX, security researchers, customers, and engineering leaders to identify high-value problems and translate them into differentiated product experiences.
Champion AI-native engineering practices, including extensive use of AI coding agents and autonomous development, testing, evaluation, and operational workflows.
Represent the team's technology and innovation with executives, customers, partners, and the broader engineering organization.
Mentor senior engineers and raise the overall engineering bar through coaching and technical leadership.