Shalini Sudarsan
Shalini Sudarsan is a DevSecOps Engineering Leader at KinderCare Learning Companies, Portland, OR, USA. Designing reliable, secure, and cost-optimized data and AI platforms. A Forbes Technology Council Member, Fellow of IETE and Women in Engineering (WIE) Oregon section, she drives enterprise AI adoption with a governed operating model that speeds time-to-market while lowering risk and spend. Shalini’s expertise spans BI strategy, data platform architecture, MLOps, observability, and value realization. She is known for translating complex engineering into measurable business outcomes. Shalini brings deep technical rigor and business expertise in the areas of DevOps and Reliability Engineering.A committed advocate for advancing technology, Shalini regularly presents at international conferences and contributes to IEEE and ACM as a technical reviewer.
Session
Scanners like Checkov and tfsec are great at flagging the misconfigurations we already have rules for, and nearly useless against the one someone introduces on purpose. After watching SolarWinds and Codecov turn CI/CD pipelines into the front door, I went looking for a better way to catch malicious changes in Terraform, Kubernetes, and GitHub Actions pairing old-fashioned syntax-tree analysis with a small language model that reads a diff in context, the way a security engineer would. This is the real story of what worked, what threw so many false positives it nearly broke developer trust, and where AI earns its keep in DevSecOps versus where it just adds noise.