Note: The job is a remote job and is open to candidates in USA. LinkedIn is the world's largest professional network, creating economic opportunity for members of the global workforce through professional connections, opportunities, skills, and insights. The company seeks a Staff Information Security Engineer to define and drive detection strategy across endpoint, identity, cloud, and SaaS environments while architecting, operating, and improving high-fidelity detection capabilities. The role provides technical leadership through security architecture, detection engineering standards, adversary emulation, mentoring, and strategic 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
- Design detections-as-code with version control, CI/CD, unit/integration tests, and staged rollouts
- Lead adversary emulation exercises to validate detection coverage; develop synthetic signal and test harnesses
- Proactive threat hunting to discover unknown attacker activity; design hunt playbooks and convert findings into detections
- Build IR automation (SOAR/Logic Apps) to orchestrate triage, enrichment, containment, and case workflow
- Operationalize threat intelligence: ingest/normalize IOCs/TTPs, enrich detections with TI context, and collaborate with TI to turn reports into testable hypotheses
- Build and maintain a SIGMA-based detection content library; translate SIGMA to KQL/SQL where applicable
- Own telemetry quality: schemas, enrichment, normalization, and data reliability SLIs/SLOs
- Establish and monitor detection quality metrics (signal-to-noise ratio, precision/recall, false-positive rate, alert latency, lift); drive continuous tuning
- Lead incident retros to add resilient post-incident detections and suppress noisy patterns
- Mentor engineers; establish standards, code reviews, and guidance for detection engineering best practices
- Participate in on-call for critical detection pipelines and high-severity investigations
Skills
- BA/BS Degree in CyberSecurity, Information Security, Computer Science or related technical discipline, or related practical experience
- 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 (AWS/Azure/GCP)
- Experience building detections and automation with scripting languages (e.g., Python) and query languages (e.g., KQL/SQL)
- Experience building detections-as-code (tests, CI/CD, canary deploys, rollback) at large scale
- Experience with attacker TTPs and frameworks (ATT&CK) and detection efficacy metrics
- Experience designing schemas and data models (e.g., ASIM/OSSEM-like) and telemetry pipelines
- Experience with SIGMA rule authoring and translation; adversary emulation/purple-team experience
- BS and 8+ years of relevant work experience, MS and 7+ years of relevant work experience, or PhD and 4+ years of relevant work experience
- 8+ years of experience in detection engineering, with 3+ years of experience in a technical leadership role
- Rigorous approach to detection quality (SNR, precision/recall, false-positive rate, latency) and measurement
- Experience operating detections over billions of events/day and multi-region data pipelines
- Building detection testing harnesses, synthetic signal, and adversary emulation at scale
- Familiarity with identity/security signals (AAD/Okta/SSO), endpoint internals (Windows/Linux/macOS), and SaaS logs
- Applied analytics/ML for anomaly detection, risk scoring, or enrichment (with robust evaluation)
- Experience building hypotheses and content for AI-enabled attack patterns; practical use of AI to improve detection engineering workflows
- Relevant certifications (e.g., GCTI, GCDA, GCFA, GIAC-blue); publications or open-source contributions in detections
Benefits
- Generous health and wellness programs for employees of all levels
- Time away for employees of all levels
- This position may also include an annual performance bonus, stock, benefits and/or other applicable incentive compensation plans
- This role may be remote or hybrid
- Remote anywhere in the United States or hybrid in LinkedIn’s Mountain View office location
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