Cybersecurity Engineer

Onsite in Toronto, ON

Job Description

Our highly coveted Engineers are interspersed amongst many areas of focus: innovation, design, execution, maintenance, strategy, and system management of our Security Information & Event management (SIEM) and security analytics platforms including but not limited to Cribl Log stream, Splunk Enterprise Security and Microsoft Sentinel. We call all these things incredible learning opportunities, and no two assignments are ever the same.

Role and Responsibilities

We are looking for a Cybersecurity engineer who is a Subject Matter Expert (SME) in security logging and monitoring of AI systems & applications. The individual should have an engineering mindset and advanced experience working on enterprise Security Information and Event Management (SIEM) tools.

This role focuses on research, development, and implementation of security logging of AI systems and applications, providing hands-on technical support at level 3 and Level 4, and implementing strategic currency and platform optimization initiatives required to address AI security logging and monitoring mandates.

You'll be playing an important role in advancing the overall design, architecture, and technological capabilities of our security logging and monitoring of AI systems & applications in alignment with best practices in the industry.

Here is some of what you may be asked to perform:

• System integration for security logging of AI system & application events to the enterprise SIEM platforms.

• Implement AI security logging strategies that ensure AI security event log data onboarded to the SIEM is useful, manageable, and easy to query while minimizing any impact on system performance.

• Research logging techniques for identifying, retrieving and monitoring security events generated by AI systems/applications

• Work with the Senior manager to plan strategic roadmap for analytics technologies in coordination with the business aspects of security engineering and Cyber Threat Management teams.

• Contribute to the strategic roadmap for the enterprise SIEM to meet business needs/requirements.

• Provide L3/L4 support when needed by the SIEM L2 teams.

• Ensure capacity and currency uplifts are planned and executed within desired timelines.

• Promote and drive automation opportunities when and where possible.

• Develop the skills to support Engineering tasks related to AI security initiatives.

• Adhere to internal policies and procedures, technology control standards, and applicable regulatory guidelines.

• Influence behavior to reduce risk and foster a strong technology risk management culture throughout the enterprise.

• Learn about new SIEM platforms and

Job Requirements

What can you bring to the team? Share your credentials, but your relevant experience and knowledge can be just as likely to get our attention. It helps if you have:

• University or Post-Graduate Degree in Computer Science/Engineering, Cybersecurity, Information systems/technology, Artificial Intelligence, or a related discipline

• 5 years+ relevant information technology and security engineering experience

• Good understanding of steps generated by LLMs before calls are made to a tool/system

• Good understanding of MITRE and other relevant AI related security framework

• Advance knowledge and experience in administering SIEM platforms such as Splunk enterprise platform, Microsoft sentinel and Google cloud log infrastructure.

• Advance knowledge of onboarding security logs to SIEM (Splunk and Microsoft).

• Advance knowledge of IT security, risk disciplines and practices, with solid understanding of cloud security.

• Strong partnership skills to ensure collaboration across a team and other lines of business as part of control execution.

• Excellent written and oral communications skills and ability to articulate and present information to senior executives, peers, all levels of technical staff, and stakeholders.

• Ability to work autonomously as an engineering specialist on high-profile, complex and/or high-risk security analytics technology initiatives.

Certifications

• Security certification required (CISSP, CCSP, CompTIA Security+, etc)

• AI-related certifications is an advantage

• Splunk admin or architecture certification is an advantage.

• Google Cloud security certification is beneficial.

• Azure security Engineer certification is an advantage.