Staff Information Security Engineer - Detection Engineering
The Staff Information Security Engineer leads detection strategy and architecture, building high-signal detections-as-code to identify adversary activity across LinkedIn's cloud and enterprise environments. The role involves hands-on engineering, adversary emulation, and mentoring to improve detection fidelity and operational efficiency.
- Compensation
- $156K–$255K / yr
- Location
- Remote, UNITED STATES, us
- Work setup
- Remote
- Seniority
- Staff
- Employment
- Contract
- Experience
- 2+ years
- Category
- Security
- Posted
Skills
Must have
- BA/BS Degree in CyberSecurity, Information Security, Computer Science or related technical discipline
- 5+ years in security engineering, detection engineering, or incident response
- 2+ years technical leadership
- Expertise with log analytics and detection content for SIEM/XDR/EDR and cloud provider telemetry
- Experience building detections and automation with scripting languages and query languages
- Experience building detections-as-code at large scale
- Experience with attacker TTPs and frameworks and detection efficacy metrics
- Experience designing schemas and data models and telemetry pipelines
- Experience with SIGMA rule authoring and translation; adversary emulation/purple-team experience
Full description
At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. This role may be remote or hybrid. At LinkedIn, hybrid roles are performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. Remote roles are performed from the designated home work location upon time of hire, and any changes to this home work location requires a review of remote status and approval.
This role can be remote anywhere in the United States or can be hybrid in LinkedIn’s Mountain View office location.
About the Team
LinkedIn’s Information Security organization protects our members, data, and platforms by building resilient security controls, detecting threats early, and partnering across engineering to reduce risk at scale.
The Detection Engineering team sits at the center of LinkedIn’s threat detection ecosystem. We partner closely with Incident Response, Threat Intelligence, Red and Purple Teams, Product Security, Identity & Access Management, and Cloud Security to identify, contextualize, and detect adversary activity across the enterprise. Beyond developing and maintaining high-fidelity detections, we drive the security telemetry strategy through log onboarding, schema design and normalization, automation, threat hunting, incident response support, and audit enablement. Our mission is to continuously improve LinkedIn’s ability to detect, investigate, and respond to evolving threats with speed and precision.
About the role
As a Staff Security Engineer on the Detection Engineering team, you will define and drive LinkedIn’s detection strategy across endpoint, identity, cloud, and SaaS environments. You will architect, build, and operate high-signal detection capabilities using modern detections-as-code practices, telemetry modeling, and data-driven effectiveness measures, including precision, recall, signal-to-noise ratio, and detection latency.
You will work from adversary tactics, techniques, and procedures (TTPs) to design resilient detection coverage, partnering with Red and Purple Teams to validate effectiveness through adversary emulation and attack simulation. As a technical leader, you will establish engineering standards, influence security architecture, mentor fellow engineers through design and code reviews, and drive strategic investments that improve detection fidelity, scalability, and operational efficiency. This is a hands-on staff-level role focused on technical leadership, architecture, and execution.
Responsibilities
- Define detection strategy and roadmap; drive coverage across priority threat scenarios and emerging attacks relevant to LinkedIn
- Partner with IR/Threat Intel/Cloud/IAM to turn hypotheses and TTPs into production detections; lead purple-team validation.