Piriyadharshan Ravi

– Led end-to-end product delivery of an LLM-powered security orchestration platform integrating multi-agent AI workflows across cloud telemetry sources, reducing incident response time by 40%. – Designed intelligent triage and automated remediation workflows that correlated alerts, logs, and operational signals, increasing incident handling throughput by 3x. – Partnered closely with platform engineers and security teams to define system architecture, success metrics, and rollout strategy from prototype to production. – Eliminated ~1,200 FTE hours annually by replacing manual escalation and diagnostic processes with LLM-assisted workflows, improving reliability and operator experience.

– Owned the core platform roadmap for autonomous retail systems processing 86K+ monthly transactions, spanning computer vision pipelines, real-time event processing, and distributed microservices. – Led performance optimization initiatives across edge devices and backend services, improving system accuracy from 72% → 93% and enabling production-grade reliability across European deployments. – Built data-driven monitoring and alerting frameworks to detect anomalies across store operations, reducing operational incidents and accelerating root-cause analysis. – Drove pricing experiments and system-level optimizations resulting in 11% MoM footfall growth and 90% GMV uplift, balancing business outcomes with platform stability. – Worked directly with enterprise retail partners as design customers, translating operational pain points into scalable product features.

– Scaled a real-time interactive platform supporting 100K+ concurrent users, owning reliability, latency, and engagement metrics. – Introduced dynamic reward and recommendation engines, increasing DAU by 44% and participation by 36%, while managing trade-offs between performance and personalization.

– Built GameStudio controller, payment engine, and broadcast pipeline; reduced streaming latency to sub 6 seconds, which resulted in real-time engagement.

– Served as SME for SmartSwipe notifications; implemented dashboards using Prometheus, Grafana, and Splunk to accelerate incident detection.