NOMINATION HIGHLIGHTS

Sushma Mahadevaswamy, Technical Leader at Cisco, has built a measurable continuous-improvement program that transforms how security is delivered across cloud, AI/ML, and application development at enterprise scale. Her work sits at the intersection of process optimization, AI-assisted automation, and DevSecOps turning reactive security into a repeatable, data-driven improvement engine.

Unified security CI/CD platform. She led development of a centralized GitHub Actions security platform integrating Trivy, Falco, SonarQube, OPA policies, Wiz, and Rapid7 embedding security directly into developer pipelines. By standardizing pipelines on reusable workflows and actions, she eliminated duplicated pipeline logic, reduced maintenance overhead, and accelerated secure delivery across teams and geographies.

AI for continuous improvement and optimization. She applies AI strategically to improve security operations not as hype, but as measurable optimization:

Token and cost optimization for LLM-based security tooling: right-sizing model usage, batching analysis, and routing tasks to appropriate model tiers to reduce cost while maintaining coverage.
Automated LLM red-team scanning (garak, ModelScan) in CI/CD for continuous model vulnerability assessment.
ML-based anomaly detection (SageMaker/Bedrock platform) for real-time IP theft and exfiltration monitoring.
Quantifiable impact:

Prevented 15,000+ potential exposure incidents by automating elimination of default VPCs across 40+ AWS accounts.
Improved security decision-making efficiency by 30% via an Application Security Metrics Dashboard (AWS + Tableau).
Improved threat detection and response by 40% through automated Splunk log integration.
Achieved 88% reduction in code vulnerabilities by embedding automated assessment into CI/CD (prior role).
Process optimization at scale. She designed vulnerability prioritization logic for Wiz across multi-cloud Kubernetes environments, reducing remediation cycle times. She authored firmwide AI/MLOps security standards mapped to MITRE ATLAS, NIST AI RMF, and OWASP LLM Top 10 giving teams a consistent baseline that improves with each release.

Field contribution. She publishes and speaks nationally (RSAC, Cybersecurity Summit, BSides) on scalable security automation. Her peer-reviewed article, Securing Agentic AI Workflows, extends this CI mindset to autonomous AI systems.

This nomination recognizes a practitioner who uses AI, automation, and disciplined process improvement to make security faster, cheaper, and more effective continuously.