I am a cybersecurity engineer specializing in AI-driven threat intelligence, detection engineering, and cloud security. I design scalable security systems and develop intelligent detection solutions to strengthen enterprise security posture.Sample text. Click to select the Text Element.
I am deeply engaged in research across AI-powered security, next-generation SIEM, and Zero Trust architectures, focused on translating advanced concepts into practical, real-world security solutions.
start a project nowRAGSec explores a next-generation approach to cybersecurity by combining Retrieval-Augmented Generation with real-time SIEM telemetry, threat intelligence, and behavioral signals. It introduces context-aware analysis, enabling deeper visibility into threats, improved correlation across diverse data sources, and a significant reduction in noise within modern security operations
By bridging advanced AI with security engineering, RAGSec redefines how threats are detected, analyzed, and prioritized. It enhances alert enrichment, supports intelligent decision-making, and lays the foundation for adaptive, scalable, and proactive security operations—inviting a deeper exploration into its architecture and real-world impact.Sample text. Click to select the Text Element.
SIEM Engineering, Detection Engineering, Threat Hunting, Incident Response, Digital Forensics, MITRE ATT&CK & MARS-E Alignment, Correlation Rule Development, Alert Tuning, False Positive Reduction.
AI/ML-based Anomaly Detection, UEBA, Behavioral Analytics, Generative AI (LLMs) for Security, Automated Alert Triage, Predictive Threat Detection, Security Data Enrichment.
Splunk, Google SecOps (Chronicle), QRadar, Sentinel, Elastic, LogRhythm, Sumo Logic, Cortex XSOAR, Splunk SOAR, Kafka, Logstash, Fluentd, Data Normalization (UDM/CIM).
Burp Suite, OWASP ZAP, Nmap, Metasploit, SQLMap, Nessus, Qualys, OpenVAS, Vulnerability Assessment, Secure Coding Analysis (SAST/DAST tools).
AWS (GuardDuty, Security Hub, WAF), Azure Defender, GCP Security Command Center, multi-cloud security architecture, Zero Trust implementation, IAM, CSPM, cloud threat detection.Sample text. Click to select the Text Element.
Linux/Unix systems, Docker, Kubernetes, Terraform, CI/CD pipelines, policy-as-code, Python, Bash, PowerShell, infrastructure automation, security orchestration.Sample text. Click to select the Text Element.
NIST CSF, ISO 27001, CIS benchmarks, PCI-DSS, HIPAA, GDPR, SOC2, risk assessment, audit & compliance, security governance frameworks.Sample text. Click to select the Text Element.
Architected and scaled enterprise SIEM platforms across hybrid and multi-cloud environments, onboarding 50+ log sources and improving security visibility by up to 80%.
Architected and scaled enterprise SIEM platforms across hybrid and multi-cloud environments, onboarding 50+ log sources and improving security visibility by up to 80%.
Led detection engineering initiatives aligned with MITRE ATT&CK, developing 100+ detection rules and enhancing coverage across advanced attack vectors.
Implemented AI/ML-driven threat detection and UEBA models, reducing false positives by up to 50% and improving detection accuracy and SOC efficiency.
Built and operationalized Detection-as-Code frameworks using Terraform and CI/CD pipelines, accelerating deployment cycles by up to 70% and enabling scalable, automated security operations.
Integrated 200+ threat intelligence feeds with SIEM and UEBA systems, enhancing correlation and improving detection of advanced threats across enterprise environments.
"RAGSec leverages Retrieval-Augmented Generation to combine LLMs with real-time SIEM telemetry and threat intelligence, enabling context-aware threat detection, enriched alert analysis, and faster, more accurate SOC decision-making."
Posted on 10th April 2026.
"Traditional SIEM struggles with contextual understanding, leading to noisy alerts and delayed responses. Integrating LLMs enables intelligent correlation, enriched insights, and faster, more efficient SOC workflows for modern threat detection environments."
Posted on 1st April 2026.
"Behavioral analytics combined with AI enables detection of unknown and evolving threats by analyzing patterns and anomalies, significantly reducing false positives and improving accuracy and efficiency across modern security operations environments."
Posted on 21st March 2026.
"AI-driven runbooks automate incident response by generating context-aware recommendations, enabling faster decision-making, reducing manual effort, and improving overall efficiency and consistency across Security Ops Center workflows."
Posted on 15th March 2026.
"Access decisions must dynamically adapt by continuously evaluating identity, behavior, and risk signals, enabling context-aware, real-time enforcement of security policies across modern, distributed and cloud-native environments.Sample text. Click to select the Text Element."
Posted on 7th March 2026.
"Without normalized telemetry, security data remains fragmented and inconsistent, making scalable detection, accurate correlation, and effective threat analysis nearly impossible across complex, distributed enterprise environments.Sample text. Click to select the Text Element."
Posted on 28th Feb 2026.
Texas,
United States
jithendrachowdary.popuri
@gmail.com
+1 9404656232
+91 9866078273
Available for remote cybersecurity consulting, vulnerability assessments, and secure development projects worldwide.