Security Engineer, Detection & Response

Responsibilities

• Own day-to-day operation of Liftoff's SIEM (Panther) — log source ingestion, detection content, and the alert investigation pipeline.
• Lead Liftoff's adoption of AI-augmented SOC tooling (e.g. Prophet, Dropzone, or equivalent) as a multi-year modernization investment.
• Triage incoming security alerts and drive timely investigation and remediation with stakeholders across Engineering and IT.
• Lead incident response — investigation, containment, and post-incident review — and mature processes and runbooks so response becomes predictable and repeatable.
• Build tooling and automation that detects active threats, enriches alerts, and reduces manual investigation toil.
• Partner with Engineering and IT to make detection and response self-service where possible — clear log-onboarding paths, documented detection proposals, accessible runbooks.
• Close the feedback loop between the team's offensive and proactive findings and detection coverage.
• Partner across the security team on cloud, infrastructure, and application security work.
• Participate in the Security team's on-call rotation and incident response.

Requirements

• 5+ years in security engineering, security operations, detection engineering, or software engineering with a security focus.
• Hands-on production SIEM operation — onboarding log sources, writing and maintaining detection content, and triaging alerts.
• Write production-quality code for security automation and detection-as-code.
• Experience leading or substantially contributing to security incident response.
• Strong technical writing — design docs, runbooks, and post-incident reviews.
• Demonstrated judgment in prioritizing security work using a risk-based approach.
• Ability to quickly navigate large, unfamiliar codebases and reason about complex engineering systems.
• Excellent verbal communication.
• Willing to participate in an on-call rotation.

Nice-to-Haves

• Hands-on experience with an AI-augmented SOC platform (Prophet Security, Dropzone AI, or equivalent), or with building large language model (LLM) augmented investigation and runbook tooling.
• Experience operating in cloud environments at scale.
• Cloud incident response experience, particularly in AWS.
• Endpoint forensics for incident response on Mac and/or Linux.
• Detection-as-code workflows in continuous integration and deployment (CI/CD) pipelines.
• Mobile adtech or high-volume SaaS background.