About Us

Signal Sciences empowers security and engineering teams by providing visible and effective web application security protecting against real-world attacks. With our unique hybrid on-premise and cloud architecture, we process, protect and report on billions of requests per day for some of the most sophisticated companies in the world ranging from Adobe to Vimeo, Taser to Under Armour. Our goal is a more secure Web, with tools people love to use, written by people who love to make them. Join us.

The Opportunity

• Helpdesk Level I/II
• Is on the Technology Operations Team
• Located in Culver City, CA.

Responsibilities

• Support local and remote employees with their day-to-day challenges.
• Learn new technologies and approaches. Think Big Picture.
• Manage access for incoming and exiting employees.
• Provision and maintain local and SaaS-based user accounts, including BetterCloud, Github Enterprise, Google Apps for Work, Slack, Confluence and other business-specific platforms
• Proactively search for potential issues or improvements and lead the charge to address them.
• Manage IT Ticketing system queues as well as End User Service Portal
• Manage configuration and hardware support of all mobile devices in an Enterprise MDM environment
• Troubleshoot issues on user systems whether they are remote or in the office
• Maintain the health of Zoom conference rooms
• Manage IT inventory and purchasing in addition to enterprise-wide asset tracking
• Help shape and enforce basic IT standard operating procedures and Security Policies as we grow our team
• Be an advocate for our Security Policies and Standard Operating Procedures.

Our New Team Member Must Have

• Minimum 1 year of support experience.
• A solid understanding of macOS and iOS (we are 100% Apple).
• A grasp on self-prioritization; the ability to balance priorities without hitting the “freak out button”.
• Patience and wherewithal to find the best solution for a problem.
• The courage to fail...and then learn from it.
• The ability to recognize the difference between thin and thick imaging, and which is appropriate for each unique circumstance.

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