Principal Active Defense Engineer

Workday•Reston, VA

4d•$167,200 - $300,000•Hybrid

About The Position

This role is the senior technical anchor for Active Defense. As a Principal Active Defense Engineer, you will set the technical direction for how Workday detects threats, and you will be the engineer the team looks to when a problem is ambiguous, spans several systems, or has no obvious owner. The breadth here is real. Our work runs from translating threat intelligence into new detections, through the quality and fidelity of the alerts we hand to incident response, to the detections-as-code pipeline, curated datasets, and CI/CD tooling that all of it depends on. We also serve as the subject matter experts other teams come to for audits, coverage questions, and platform decisions. You will be expected to operate across that whole surface rather than in one corner of it. The engineers who do best in this seat tend to come from a strong software, platform, or data engineering foundation applied to security, rather than from a purely analytical security path. You will lead large initiatives from concept to production with little direction, and you will decide how we apply AI-assisted analysis, automation, and agents to detection work. This is a team early in its growth, so the standards you set will be adopted broadly and quickly, and raising the technical ceiling of the engineers around you through mentorship, design review, and the standard your own work sets is a core part of the job. This is a hands-on engineering role rather than a people management role.

Requirements

Depth in detection engineering: 10+ years in software, platform, or security engineering, including significant time building and operating detection or security capabilities at production scale.
Technical leadership as an individual contributor: Experience setting technical direction, leading complex multi-system initiatives, and raising the level of the engineers around you through design and code review, without managing people.
Software development expertise: Experience in a general-purpose programming language such as Python, Java, Kotlin, Scala, or JavaScript, used to build detection logic, tooling, and automation.
Detection platform ownership: Experience architecting a detections-as-code pipeline, detection platform, or production data pipeline that other engineers build on, rather than working within one someone else built.
AI-assisted engineering judgment: Experience applying generative AI, conversational AI, or AI agents to security engineering work, including cases where you concluded the AI-assisted approach was the wrong one.
Platform and cloud breadth: Experience with SIEM platforms such as Splunk, and with developing, securing, and monitoring applications in public cloud environments.

Nice To Haves

Production engineering discipline: Experience with automated testing, validation, and deployment for detection content, not only version control.
Threat-informed detection: Experience translating threat intelligence, adversary techniques such as those in MITRE ATT&CK, and incident learnings into durable detections, and verifying that those detections fire.
Adaptive detection analytics: Familiarity with behavioral baselines, entity-level context, anomaly detection, or risk-based alerting.
Cross-team technical leadership: Experience serving as the subject matter expert for partner teams, audits, and compliance or customer inquiries.
Program judgment: Proven ability to run several complex technical projects at once across competing priorities and ongoing operations.
Communication: Strong communication skills and the ability to present technical information to a non-technical audience.
Continuous learning: Enthusiasm for emerging work in security, data science, and machine learning, with the judgment to know what is worth adopting. Relevant certifications or training such as SANS or CISSP are useful but not required.

Responsibilities

Set the technical direction. Own the architecture decisions, detection methodology, and design standards for the detection portfolio and the platform it runs on.
Be the review authority. Serve as the senior reviewer for infrastructure changes and complex detections, so that design and code review is a fast path for the team rather than a queue.
Lead large initiatives through to live operation. Take ambiguous problems from concept all the way to running in production, including the validation, documentation, and response playbook that make an alert worth acting on.
Build for reuse. Advance the detections-as-code lifecycle, CI/CD, validation tooling, and curated datasets, turning one-off solutions into patterns the whole team adopts.
Raise the technical ceiling of the team. Mentor engineers through design review, code review, and pull request feedback so that judgment and delivery scale beyond any one person.
Lead how we apply AI. Determine where agents, automation, and generative tooling belong in authoring, validating, and tuning detections, and where they do not.
Own detection quality. Drive coverage, fidelity, and noise reduction so that the alerts reaching our incident responders are worth their attention.
Represent detection engineering across Workday. Partner with incident response, threat intelligence, security tooling, audit, and platform teams, and serve as the expert voice on detection coverage and capability.
Shape what comes next. Evaluate emerging detection approaches, platforms, and vendors, and bring in what measurably improves outcomes.