Artificial Intelligence (AI) Cybersecurity Analyst

Job Description: We are seeking a talented and experienced Artificial Intelligence (AI) Cybersecurity Analyst to join our dynamic team. The ideal candidate will have a strong background in cybersecurity, with expertise in applying artificial intelligence and machine learning techniques to enhance threat detection, incident response, and security operations. As an AI Cybersecurity Analyst, you will play a key role in developing and implementing AI-driven security solutions to safeguard our clients' digital assets and mitigate cyber risks.
Responsibilities:

• Utilize artificial intelligence and machine learning algorithms to analyze security data, detect anomalies, and identify patterns indicative of cyber threats.
• Develop and refine AI models and algorithms for threat detection, including supervised and unsupervised learning techniques, anomaly detection, and behavioral analysis.
• Collaborate with cross-functional teams to define use cases, requirements, and success criteria for AI-driven cybersecurity solutions.
• Design and implement AI-based security tools and systems to enhance threat detection, incident response, and security operations.
• Conduct research and experimentation to evaluate emerging AI technologies and methodologies for cybersecurity applications.
• Monitor and analyze security events and alerts generated by AI-driven security systems, investigate potential threats, and coordinate incident response activities.
• Stay updated on the latest advancements in AI, machine learning, and cybersecurity research, and apply them to enhance our cybersecurity capabilities.
• Provide technical expertise and guidance to clients and internal teams on leveraging AI for cybersecurity, including training, best practices, and implementation strategies.

• Bachelor's degree in Computer Science, Information Security, or related field. Advanced degree (Master's or Ph.D.) preferred.
• Experience in cybersecurity, with a focus on artificial intelligence, machine learning, or data science.
• Proficiency in programming languages such as Python, R, or Java, and experience with AI/ML libraries and frameworks (e.g., TensorFlow, scikit-learn, PyTorch).
• Strong understanding of cybersecurity principles, technologies, and best practices, including threat intelligence, incident response, and security operations.
• Experience with data preprocessing, feature engineering, model training, and evaluation for cybersecurity applications.
• Excellent problem-solving skills, analytical thinking, and attention to detail.
• Strong communication and collaboration abilities, with the ability to work effectively in multidisciplinary teams and communicate complex technical concepts to non-technical stakeholders.

• Certified Information Systems Security Professional (CISSP)
• CompTIA Cybersecurity Analyst (CySA+)
• Certified Ethical Hacker (CEH)
• AWS Certified Security – Specialty
• Certified Information Security Manager (CISM)

• Adversarial Machine Learning: Understanding of adversarial machine learning techniques and methodologies, including adversarial examples, evasion attacks, and poisoning attacks, can enable the development of robust AI models that are resilient to adversarial manipulation and exploitation.
• Threat Hunting: Proficiency in threat hunting techniques and methodologies, including proactive searching and investigation of security threats and indicators of compromise (IOCs), can help identify and mitigate sophisticated and stealthy cyber threats before they escalate into full-blown incidents.
• Security Automation and Orchestration: Experience with security automation and orchestration platforms such as SOAR (Security Orchestration, Automation, and Response) tools can streamline security operations, automate routine tasks, and orchestrate incident response workflows using AI-driven playbooks and workflows.
• Cloud Security: Knowledge of cloud security principles, architectures, and best practices, as well as experience with securing cloud environments such as AWS, Azure, or Google Cloud Platform (GCP), can facilitate the integration of AI-driven security solutions into cloud-native environments and services.
• Network Security: Understanding of network security concepts and protocols, including firewalls, intrusion detection and prevention systems (IDS/IPS), and network traffic analysis (NTA), can enable the development of AI-driven solutions for detecting and mitigating network-based cyber threats.
• Endpoint Detection and Response (EDR): Familiarity with endpoint security solutions and EDR platforms, as well as experience with AI-driven endpoint detection and response techniques, can enhance the visibility, detection, and remediation of threats targeting endpoint devices and systems.
• Incident Response Forensics: Knowledge of digital forensics principles and methodologies, including evidence collection, preservation, and analysis, can support incident response efforts and facilitate the identification and attribution of cyber adversaries through AI-driven forensic analysis.
• Regulatory Compliance: Awareness of regulatory frameworks and compliance requirements related to cybersecurity, privacy, and data protection, such as GDPR, HIPAA, or PCI DSS, can help ensure that AI-driven security solutions adhere to legal and regulatory standards and requirements.
• Soft Skills: Strong interpersonal skills, teamwork, communication, and stakeholder management abilities are essential for collaborating effectively with cross-functional teams, communicating security findings and recommendations to diverse audiences, and building trust and credibility with clients and stakeholders.
• Continuous Learning: Commitment to continuous learning and staying updated on emerging trends, technologies, and advancements in AI, machine learning, and cybersecurity through training, certifications, and participation in industry conferences and events is crucial for remaining at the forefront of innovation and driving continuous improvement in AI-driven cybersecurity solutions.