Principal Software Engineer & Architect, Cyber Defense Engineering

ServiceNow•Santa Clara, CA

About The Position

The Principal Software Engineer & Architect will own the technical direction of data and platform systems supporting Cyber Defense Engineering, including detection, investigation, hunting, response, and AI-driven defense. The role is responsible for the architecture of a multi-system security data platform, from ingestion through access, and for ensuring that data is consistent, trustworthy, and useful across people, automation, and AI. Multiple engineering teams will build against this architecture, and the role's decisions are expected to contribute to measurable security outcomes. The position establishes a secure, scalable data foundation for security operations and applied AI, while guiding technical design across teams. It also sets engineering standards, documents major decisions, mentors engineers, and connects platform investment to outcomes such as detection coverage, time to detect and respond, and data quality and freshness.

Requirements

Bachelor's degree in computer science, software engineering, or a similar field.
10+ years of software engineering experience, including 3+ years in a principal, staff, or architect role.
Proven experience designing and operating large-scale cloud data platforms in production, including data modeling, data warehouse design, and high-volume streaming and batch telemetry pipelines across multiple systems.
Hands-on ML/AI experience, including shipping ML- or LLM-based systems to production, and working knowledge of how data quality, freshness, and lineage affect model performance.
Proficiency in SQL and at least one general-purpose programming language: Python, Go, or Java.
A record of setting technical direction across teams without formal authority.
Clear, concise writing and a habit of documenting decisions and their rationale.

Nice To Haves

Experience applying ML and graph-based analysis to security problems, such as anomaly detection, entity correlation, incident investigations, or attack path analysis.
Experience in security operations, such as SIEM platforms, security datalakes, detection engineering, or incident response.
Knowledge of secure data access patterns such as RBAC/ABAC, masking, and policy-as-code.
Advanced degree in machine learning, AI, or a related field.

Responsibilities

Own the architecture of the multi-system security data platform, from ingestion to access, supporting detection, investigation, hunting, and risk analytics.
Determine where data should reside by weighing business value, performance, retention, and cost, and reduce duplication across systems.
Define shared schemas, data models, and data contracts to make telemetry consistent, trustworthy, and joinable for people, automation, and AI.
Build the data foundation for AI in security operations, including data and feature pipelines, model evaluation, retrieval, and governed data access for AI agents.
Incorporate access control, data protection, auditability, and compliance into the platform architecture.
Lead technical design across teams, resolve shared-platform tradeoffs, and maintain coherent architecture as the organization grows.
Drive major technical decisions to closure through design and decision documents.
Set engineering standards for source control, CI/CD, testing, and observability.
Mentor engineers through design and code reviews.
Connect platform investments to measurable outcomes, including detection coverage, time to detect, investigate, and mitigate, and data quality and freshness.