SOC Support Specialist
New
H
HuntressCybersecurity
Location: Remote US, Pacific or Mountain Time ZonesFull-TimeEntry
Salary$50,000 to $65,000 base plus bonus and equity; this role may be eligible for on-call/call-in pay in addition to base pay
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Job Details
- Required Skills
- CybersecurityZendeskCustomer support
Requirements
- Must be able to work Tuesday through Saturday.
- Demonstrated passion for cybersecurity, including identity compromise, phishing, incident response, and endpoint security.
- Exceptional written and verbal communication skills.
- Ability to remain calm, empathetic, and solution-focused during active security incidents.
- Interest in developing incident management skills, including owning information flow and driving incidents to resolution.
- Ability to prioritize and manage a dynamic ticket queue.
- Strong self-awareness and ability to work independently in a remote setting.
- MSP or Help Desk experience is a plus.
- Microsoft 365/Entra experience is a plus.
- Basic understanding of SIEM concepts and log analysis is a plus.
- Basic understanding of networking concepts related to VPNs, IP addresses, and usage anomalies is a plus.
Responsibilities
- Provide exceptional customer support via phone, email, and chat for Huntress incident reports, escalations, and SIEM-related questions.
- Ensure partner understanding by breaking down complex SOC concepts, log data, and product behavior into digestible, actionable guidance.
- Lead calls with partners for high-severity or complex incidents, facilitating clear communication, documenting decisions, and aligning on next steps.
- Collaborate effectively with Product Support, Security Operations Center, and other internal teams to clarify detection coverage, data gaps, and product behavior.
- Troubleshoot product issues and provide support for other product-related requests as needed.
- Advocate for partner needs and provide feedback to the relevant internal teams.
- Contribute to the development of knowledge base articles, macros, and internal runbooks based on real ticket patterns.
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