Security Engineer - Incident Response

About the Role

We're looking for a Security Engineer with deep incident response experience to help defend Replit, a fast-moving, cloud-native AI vibe-coding platform. You'll be the person who takes charge when something goes wrong. You'll lead investigations from first signal to root cause, coordinate containment across Security, SRE, and Engineering, and keep stakeholders informed while the incident is moving fast.

This isn't a pure responder role. We want a well-rounded security engineer who has run real incidents and wants to make the next one faster. You'll write the scripts, automations, and tooling that take manual work out of triage, evidence collection, and containment. You'll also turn lessons from each incident into better detections, playbooks, and platform hardening.

Responsibilities

Incident Response

• Serve as incident commander or technical lead for security incidents, from detection and triage through containment, eradication, recovery, and post-incident review.
• Coordinate response across Security, SRE, Engineering, Legal, and leadership. Drive decisions under pressure and keep a clear record of actions taken.
• Communicate incident status, impact, and risk clearly to technical and executive audiences.
• Participate in and help shape the security on-call rotation.

Investigation & Forensics

• Investigate suspicious activity across cloud infrastructure, containers, identity systems, and application layers using SIEM, Cloud Logging, telemetry, and host and container artifacts.
• Determine scope, root cause, attacker behavior, and blast radius for confirmed incidents.
• Quickly assess whether emerging threats (0-days, active exploitation campaigns, bug bounty findings, customer reports) apply to Replit, and whether we're already affected.

IR Automation & Tooling

• Build scripts, automations, and tools (Python, Go, Bash, or directly on Replit) that speed up response, such as automated enrichment, evidence collection, credential and session revocation, workload isolation, and alert triage.
• Develop and maintain response playbooks and runbooks, and automate them where possible.
• Integrate response workflows with SIEM, SOAR, ticketing, and chat tooling to cut time-to-contain.

Detection & Continuous Improvement

• Turn incident findings into new or improved detections, logging coverage, and visibility.
• Lead blameless post-incident reviews and drive remediation items to completion.
• Run tabletop exercises and simulations to test readiness and find gaps.

Required Skills & Experience

• Proven experience leading or serving as technical lead on security incidents in a cloud or SaaS environment.
• Strong hands-on investigation skills with SIEM, cloud audit logs, and log-based analysis. Comfortable working through large datasets under time pressure.
• Proficiency writing production-quality scripts or tools in Python, Go, or Bash for investigation and automation.
• Solid knowledge of cloud architecture and security, especially Google Cloud Platform (IAM, audit logging, GKE, networking).
• Working knowledge of Kubernetes and containers, including how to investigate and contain compromised workloads.
• Understanding of identity systems, SaaS architectures, and common cloud attack paths (credential theft, privilege escalation, supply chain, token abuse).
• Familiarity with software engineering fundamentals, CI/CD pipelines, and package ecosystems, so you can work effectively with Engineering on code-level fixes.
• Understanding of IR frameworks and lifecycle (for example NIST 800-61), plus the vulnerability lifecycle and exploitability analysis.

Preferred Qualifications

• Experience building or operating SOAR or other response automation platforms.
• Digital forensics experience with cloud, Linux hosts, or containers.
• Experience with threat intelligence, threat hunting, or security research.
• Experience with bug bounty programs or coordinated vulnerability disclosure.
• Familiarity with detection-as-code practices and writing detection rules.
• Experience in fast-paced, cloud-native, or AI/ML-driven environments.
• Relevant certifications (such as GCIH, GCFA, GCFR), or equivalent hands-on experience.