Threat Intelligence Analyst - AI ML Project

Job Title: Cyber Threat Management Specialist II with exposure to AI ML Duration: Long-term (24+ Months) Location: Remote - Washington DC

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Job Requirement: Threat Management Specialist (Tier 2) The Tier 2 Analysts perform deep-dive incident analysis by correlating data from various sources and determines if a critical system or data set affected. Handle incidents as defined in Playbooks and SOPs. They also advise on remediation actions and provide input and analysis on how to leverage Artificial Intelligence, Machine Learning, and SOAR capabilities to improve CSOC efficiency and accuracy Must Have: 3+ years IT security experience with at least some exposure to AI/ML projects 2+ years’ experience in network traffic analysis Strong working knowledge of: Boolean Logic, TCP/IP Fundamentals, Network Level Exploits, Threat Management Strong understanding of common IDS/IPS architectures and implementations Key Responsibilities: Identification of Cybersecurity problems which may require mitigating controls Analyze network traffic to identify exploit or intrusion related attempts Recommend detection mechanisms for exploit and or intrusion related attempts Provide subject matter expertise on network-based attacks, network traffic analysis, and intrusion methodologies Escalate items which require further investigation to other members of the Threat Management team Execute operational processes in support of response efforts to identified security incidents Utilize AI/ML-based tools and techniques to detect anomalies, automate incident triage, and improve threat intelligence Performing and analyzing threat intelligence to assess risk and adapt defenses using ML enhance tools Manage email security using ProofPoint, monitor for threats, and promptly respond to attacks Configure Splunk for log analysis, create alerts, and investigate security incidents diligently Set up FirePower for network monitoring, analyze traffic patterns, and enforce robust security measures Deploy Sentinel 1 agents efficiently, monitor alerts closely, and conduct thorough security assessments Monitoring, reviewing, and responding to security alerts and incidents across multiple platforms including Microsoft Defender for Cloud Apps, Defender for Endpoint, Defender XDR, Defender for Office 365, Azure Entra ID, and Google Cloud Security Command Center (SCC) Performing threat detection and analysis, investigating suspicious activity, coordinating incident response efforts, and implementing remediation actions Tuning security policies, maintaining visibility into cloud and endpoint environments, and supporting continuous improvement of the organization’s security posture Stay current on the latest cybersecurity trends, threat actors, and AI/ML research relevant to the field Identify and support automation use cases, including the use of AI/ML to enhance SOC capabilities. Collaborate across Operations to provide SOC enhancement capabilities through the use of automation and AI. Qualification Requirements: 3+ years IT security experience with at least some exposure to AI/ML projects 2+ years’ experience in network traffic analysis Strong working knowledge of: Boolean Logic, TCP/IP Fundamentals, Network Level Exploits, Threat Management Knowledge of Control Frameworks and Risk Management techniques Strong understanding of IDS/IPS technologies, trends, vendors, processes and methodologies Strong understanding of common IDS/IPS architectures and implementations Strong understanding of IDS/IPS signatures, content creation and signature characteristics including both signature and anomaly-based analysis and detection Experience with cloud security (AWS, Azure, GCP) Hands-on experience with cybersecurity automation (e.g., SOAR platforms). Proficiency in using machine learning frameworks to develop, train, and deploy models for anomaly detection, threat intelligence, and behavioral analysis in cybersecurity contexts. Skills in data analysis and feature engineering, with the ability to preprocess and transform large datasets from various sources (e.g., logs, network traffic) to extract relevant features for machine learning models aimed at identifying security incidents and vulnerabilities. Familiarity with the application of AI/ML techniques in cybersecurity, including but not limited to automated threat detection, incident response automation, and predictive analytics. Experience in evaluating the effectiveness of AI/ML solutions in a SOC environment is a plus. Understanding and experience identifying and implementing automation use cases. Experience A minimum of eight (8) to twelve (12) years’ relevant experience. A degree from an accredited College/University in the applicable field of services is required. If the individual's degree is not in the applicable field, then four additional years of related experience is required. One or more rele