Kumar Vikramjeet is a Sr. Cyber Threat Hunter at Adobe in San Jose with 11 years of experience blending hands-on security engineering, ML-driven detection, and threat intelligence to harden large-scale enterprise environments. He has driven 40+ hunt findings and 30+ durable detections, led novel adversary investigations with no playbooks, and pivoted his team from static rules to dynamic UEBA-powered anomaly detection at scale. His work spans CI/CD automation, Python-based detection pipelines, SPL/SQL/Mongo query expertise, and adoption of GenAI to cut hunt cycles by over 30%. Previously he built ML classifiers and contributed an open-source anomaly framework and a patent-quality risk-based alerting approach, demonstrating a mix of research rigor and production delivery. Known for mentoring analysts and presenting research at major conferences, he combines academic training from Carnegie Mellon with a practical track record of turning weak signals into operational detections.
11 years of coding experience
7 years of employment as a software developer
Bachelor of Technology (B.Tech.), Computer Science and Engineering, Bachelor of Technology (B.Tech.), Computer Science and Engineering at Shri Mata Vaishno Devi University
Master's Degree, MSIT-IS, Master's Degree, MSIT-IS at Carnegie Mellon University
Python Framework to make trades with Robinhood Private API
Contributions:4 PRs, 3 pushes, 1 branch in 8 months
apipythontrading-botprivate-apitrading
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