Director of Engineering, AI Security Incubation & Innovation
ServiceNow
- Location
- Santa Clara, CALIFORNIA, United States
- Employment
- Full Time
- Work model
- On-Site
- Level
- Staff
- H-1B history
- 185 approvals (FY2023)
- Posted
- 1h ago
Skills
About this role
Director of Engineering, AI Security Incubation & Innovation Full-time Employee Type: Regular Region: AMS - North America and Canada Work Persona: Flexible or Remote Company Description 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.
Job Description
About the Team: 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. What you get to do in this role Lead a high-impact engineering team chartered to reimagine cybersecurity through AI, creating AI-native products and capabilities that fundamentally change how security teams detect, investigate, prioritize, and respond to threats. Drive zero-to-one innovation, rapidly translating emerging AI technologies and new ideas into prototypes, validated concepts, and production-grade enterprise solutions. 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. Build autonomous and agentic security experiences that can reason over security context, orchestrate tools and workflows, and take appropriate actions with minimal human intervention. Remain deeply engaged technically, providing architectural leadership and hands-on guidance on critical technology decisions, prototypes, and implementations. Establish rapid experimentation and development practices that enable the team to learn, iterate, and deliver at startup speed while meeting enterprise requirements for security, reliability, scalability, and governance. Partner closely with Product, UX, security researchers, customers, and engineering leaders to identify high-value problems and translate them into differentiated product experiences. Build and develop a team of exceptional engineers with strong backgrounds in AI/ML, distributed systems, and cybersecurity, creating a culture of technical excellence, experimentation, and bold innovation. 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. To be successful in this role, you have 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. A proven track record of building innovative AI-native products from the ground up, ideally taking new concepts from experimentation through enterprise-scale production. Strong understanding of agentic architectures, including planning and reasoning, tool use, context and