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Salary: USD 221,200 - 387,100 / annual
ServiceNow's Security and Risk Engineering organization is seeking a Principal Software Engineer to define the technical vision and architecture for AI-native security solutions. This is a high-impact role where you'll explore and apply emerging AI capabilities—including frontier models, agentic AI, reasoning, retrieval, and advanced ML techniques—to solve complex cybersecurity problems in fundamentally new ways, not simply augment existing products with AI.
You will define technical architecture and engineering standards that improve scalability, reliability, performance, and maintainability. You'll partner closely with Product, UX, security researchers, customers, and engineering leaders to identify high-value problems and translate them into differentiated product experiences. A key part of this role is championing AI-native engineering practices, including extensive use of AI coding agents and autonomous development, testing, evaluation, and operational workflows.
You'll represent the team's technology and innovation with executives, customers, partners, and the broader engineering organization. You'll also mentor senior engineers and raise the overall engineering bar through coaching and technical leadership.
The Security and Risk Engineering organization is described as a dynamic group of builders, thinkers, and problem-solvers dedicated to delivering scalable, world-class AI-powered security solutions. 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 security and risk products.
You'll need 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. You must 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 are essential. Executive-level communication skills and the ability to articulate a compelling technical vision to engineers, customers, and senior leadership are required.
REQUIREMENTS:
- 15+ years of software engineering experience, including significant technical and engineering leadership responsibility
- Deep technical expertise in modern AI/ML with demonstrated experience building production AI systems using LLMs, foundation models, agentic architectures, RAG, embeddings, knowledge retrieval, and model evaluation
- 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
- Experience designing and building highly performant and scalable distributed systems
- Required technical skills: React, Node.js, Python, Java, REST, GraphQL, SQL, AWS, Azure, GCP, Docker, and Kubernetes
- Strong proficiency in Python and experience with modern AI frameworks and infrastructure; experience with Java, Go, or similar languages is valuable
- 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 and Kubernetes is a must, along with modern DevOps practices
- Experience in cybersecurity products or deep familiarity with modern security architectures and security operations is strongly preferred
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline, or equivalent practical experience
