Responsibilities:
- AI-Driven Security Automation:Develop and implement AI-powered automation tools to detect, analyze, and mitigate security threats in real-time.
- Compliance Monitoring & Enforcement:Utilize AI/ML to automate compliance monitoring, ensuring adherence to regulatory and industry standards such as SOC 2, ISO 27001, and GDPR.
- Threat Intelligence & Anomaly Detection:Leverage AI to analyze network and system activity, identifying abnormal behavior patterns and potential security breaches before they escalate.
- Continuous Risk Assessment:Develop machine learning models that continuously assess security risks across cloud and on-premise environments, providing real-time insights and recommendations.
- Identity and Access Management (IAM):Implement AI-based analytics to detect anomalous access patterns and enforce dynamic access control policies.
- End-to-End Security Integration:Collaborate with Security, DevOps, and Compliance teams to integrate AI solutions into security monitoring, log analysis, and vulnerability management tools.
- Self-Healing Security Systems:Design and implement AI-driven remediation mechanisms that can automatically patch vulnerabilities and mitigate security risks.
- Data Protection & Encryption:Apply AI techniques to enhance data protection strategies, detecting unauthorized access and preventing data exfiltration.
- Security Posture Optimization:Continuously evaluate and refine AI-driven security models to adapt to emerging threats and evolving compliance requirements.
Requirements:
- 5+ years of experience in Security Engineering, Compliance, or DevSecOps roles with a focus on automation.
- Strong understanding of cybersecurity principles, compliance frameworks, and risk management.
- Hands-on experience in applying AI/ML techniques to security and compliance challenges.
- Proficiency in Python, with experience developing security automation scripts.
- Familiarity with cloud security best practices across AWS, GCP, or Azure.
- Knowledge of AI/ML frameworks like TensorFlow, PyTorch, or Scikit-learn.
- Experience with infrastructure automation tools (Terraform, Ansible) for security enforcement.
- Understanding of identity and access management, zero-trust security models, and behavioral analytics.
- Familiarity with CI/CD security integrations and DevSecOps methodologies.
Preferred Qualifications:
- Certifications in Security (CISSP, CEH, OSCP) or Cloud Security (AWS Security Specialty, GCP Professional Security Engineer).
- Experience with AI-driven security platforms such as Darktrace, Vectra AI, or Exabeam.
- Knowledge of cryptography, secure coding practices, and application security.
- Hands-on experience implementing AI-enhanced threat detection systems.
