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Niche senior role reduces applicant density despite metro location and recognizable bank brand.
Requires deep cybersecurity and adversarial ML domain expertise, limiting cross-industry transferability.
Explicit 15+ years, mandatory cybersecurity ML expertise, and specific security platform requirements make filters very strict.
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Lead design and development of AI/ML models for cybersecurity use cases such as anomaly detection, threat prediction, and behavioral analytics.
Maximize and extend AI capabilities embedded within enterprise security platforms (SIEM, SOAR, XDR, EDR, firewalls, DLP) for proactive threat prevention and automated protection.
Collaborate with SOC, engineering, and threat intelligence teams to operationalize AI-driven security workflows, ensuring model governance and continuous enhancement.
15+ years of experience in cybersecurity with strong exposure to AI/ML applications.
Hands-on experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) and programming in Python.
Experience working with SIEM, SOAR, XDR, EDR, and other security platforms featuring embedded AI.
Job location: Bangalore; Role type: Hybrid.
Deep expertise in AI/ML application across cybersecurity prevention, protection, detection, and response domains.
Proven capability to integrate and enhance AI features within existing security infrastructure and tools.
Strong collaborator experienced in working with SOC, perimeter security, threat intelligence, and engineering teams to build scalable AI-driven defenses.