As an AI Security Engineer, you’ll design, implement, and optimize machine-learning systems that identify, predict, and respond to cyber threats in real time.
Key Responsibilities
Develop, train, and deploy machine-learning models for anomaly detection, behavioral analysis, and intrusion prevention.
Integrate AI modules with Segura’s core threat-intelligence engine and API systems.
Conduct data preprocessing, feature engineering, and model evaluation using large-scale telemetry data.
Implement automated learning pipelines for continuous model improvement.
Contribute to research and whitepapers on emerging AI-security technologies.
Ensure models comply with ethical AI and data-privacy standards.
Collaborate with SOC analysts to fine-tune detection accuracy and reduce false positives.
Required Skills & Experience
Bachelor’s or Master’s degree in Computer Science, Data Science, or Cybersecurity (or equivalent).
2–5 years of experience in applied AI, ML, or cybersecurity engineering.
Strong proficiency in Python, with libraries such as TensorFlow, PyTorch, or Scikit-learn.
Familiarity with network traffic analysis, endpoint telemetry, or malware behavior modeling.
Experience with cloud environments (AWS, Azure, or GCP).
Understanding of threat intelligence frameworks (MITRE ATT&CK, STIX/TAXII).
Excellent problem-solving, analytical, and documentation skills.
Preferred (Nice to Have)
Experience in MLOps and model lifecycle management.
Familiarity with vector databases, real-time streaming, or SIEM tools.
Published research or open-source contributions in cybersecurity or AI.
Knowledge of Zero-Trust architecture and secure API design.
What We Offer
Competitive salary and performance bonuses.
Flexible hybrid or remote working environment.
Health, wellness, and learning benefits.
Access to cutting-edge AI infrastructure and training resources.
Opportunity to work on a mission-driven global security platform.
