Description:
Position Overview: The XDR/SIEM Integration Specialist will be responsible for designing, implementing, and optimizing XDR (Extended Detection and Response) and SIEM (Security Information and Event Management) solutions. This role involves integrating AI and ML models to enhance threat detection and response capabilities, ensuring that our security infrastructure is robust and adaptive.
Key Responsibilities:
Integration and Implementation:
- Design and deploy XDR/SIEM solutions to integrate with existing security tools and infrastructure.
- Configure and customize XDR/SIEM platforms to meet organizational needs.
AI & ML Integration:
- Integrate AI and ML models to improve threat detection, behavioral analysis, and incident response.
- Develop and implement custom AI/ML models for specific security use cases.
Monitoring and Analysis:
- Monitor the performance of XDR/SIEM systems and integrated models.
- Analyze security events and incidents to identify and respond to potential threats.
Troubleshooting and Support:
- Provide technical support for XDR/SIEM systems and resolve integration issues.
- Collaborate with IT and security teams to address performance and operational challenges.
Documentation and Reporting:
- Maintain detailed documentation of configurations, integrations, and processes.
- Generate reports and dashboards to communicate security status and incidents to stakeholders.
Optimization and Improvement:
- Continuously refine and optimize XDR/SIEM configurations and AI/ML models.
- Stay updated with the latest security trends and technologies to enhance system effectiveness.
Qualifications:
Education: Bachelor’s degree in Computer Science, Information Security, Data Science, or a related field. Advanced certifications or a Master’s degree is a plus.
Experience:
- 5+ years of experience in cybersecurity, with a strong focus on XDR/SIEM systems.
- Proven experience in integrating and optimizing security solutions, including AI and ML models.
Technical Skills:
- Proficiency in XDR/SIEM platforms (e.g., Splunk, ArcSight, QRadar).
- Experience with AI/ML models and integration in security contexts.
- Strong understanding of security principles, data analysis, and threat detection.
Additional Skills:
- Excellent problem-solving and analytical skills.
- Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders.
- Ability to work independently and as part of a team.