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
- 10+ years of software engineering experience, including leading the design and delivery of complex production systems
- Demonstrated experience as the technical owner or lead for a major system or across teams
- Depth building AI/ML-powered production systems, probabilistic modeling, graph analytics, or calibration and evaluation is a strong plus
- Modern AI experience: LLMs, RAG, embeddings, vector search, agentic harness and workflows, model evaluation, or AI observability
- Strong programming experience in Python and/or Java, Go, or a similar language
- Cloud-native technologies, distributed systems, APIs, databases, and scalable 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 Senior Staff Engineer, you own the architecture of an security harness with novel exploitability engine end to end, and you’re accountable for the decisions that shape everything downstream. You set technical direction, make the hard calls defensible, and multiply the engineers around you.
What you’ll own
- The end-to-end architecture of the exploitability engine—from evidence ingestion and entity resolution, through the attack-path probability core and choke-point ranking, to the validation loop that keeps predictions honest.
- The decisions that cascade through the system: calibrated probability versus ordinal rank,...
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