It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. Backed by Greylock and Sequoia.
About the role
This is a zero-to-one incubation. We’re building a new class of exposure analysis that ranks security work by exploitability—where an attacker could realistically get in—rather than raw severity. The architecture is evolving, and this role helps define what good looks like.
What they're looking for
- 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
- Experience leading technical initiatives spanning multiple teams without direct authority
- Demonstrated ability to design systems that scale to enterprise workloads
- Hands-on experience with frontier LLMs, agent frameworks, retrieval and vector technologies, and model evaluation and observability, probabilistic modeling or graph analytics is a strong plus
- Strong backend engineering experience with distributed systems, APIs, microservices, and cloud-native architectures
More about this role
About the team
The Security and Risk Engineering organization builds scalable, AI-powered security solutions that reduce risk and protect ServiceNow and its customers. We value AI-first thinking, clean architecture, intuitive experiences, and a culture of continuous learning.
This is a zero-to-one incubation. We’re building a new class of exposure analysis that ranks security work by exploitability—where an attacker could realistically get in—rather than raw severity. The architecture is evolving, and this role helps define what good looks like.
The role
As a Principal ML Engineer, you set the technical vision for exploitability-based security across the portfolio—not just one engine. You define the hardest modeling problems worth solving, set the direction other staff and senior engineers build within, and represent the work to executives, customers, and the broader engineering organization.
What you’ll own
- The technical vision and architecture for exploitability-driven security: where the engine goes next, and the class of problems it should solve beyond any single release.
- The hardest unsolved modeling problems—how calibrated attack-path probability holds up across...
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