Opportunity brief
Responsibilities: Develop AI-powered solutions for log analysis and security event monitoring. Build automation workflows for SOC operations, alert triage, and incident response. Analyze logs from firewalls, endpoints, servers, cloud platforms, and SIEM solutions to identify anomalies and potential threats. Design and implement Machine Learning or LLM-based models for cybersecurity use cases. Develop Python-based tools for parsing, correlating, and processing security logs. Integrate AI solutions with SIEM, EDR, cloud, and security monitoring platforms using APIs. Create dashboards and reports to visualize security insights and AI-generated recommendations. Conduct research on emerging AI applications in cybersecurity and evaluate new techniques. Document technical findings and collaborate with the engineering team on product development. Requirements: Pursuing or recently completed a degree in Computer Science, Information Security, Artificial Intelligence, Data Science, or a related field. Strong programming skills in Python . Basic understanding of cybersecurity concepts, including network security, SOC, SIEM, logs, and incident response. Familiarity with Machine Learning fundamentals and AI frameworks such as Scikit-learn , TensorFlow , or PyTorch . Knowledge of Large Language Models (LLMs) , prompt engineering, or AI agents is a plus. Understanding of Linux, REST APIs, Git, and SQL/NoSQL databases. Strong analytical and problem-solving skills with an interest in security automation. Good communication skills and the ability to work independently in a research-driven environment. Experience with cloud platforms (AWS, Azure, or GCP), Docker, or Kubernetes is an added advantage.