Glen Waverley, Victoria, Australia
20 years of architecting secure, automated AI infrastructure. I am driven by a single mission: Enhancing the resilience of hyperscale AI superclusters. As AI scaling hits critical communication and reliability bottlenecks, I am deep-diving into the evolution of GPU-based observability—from kernel-level telemetry to topology-aware diagnostics. My expertise lies in blending Enterprise Automation with Predictive Failure Analysis to ensure high-performance fabrics remain resilient under mission-critical workloads. Areas of Interest & Research: GPU Fabric Modeling: Decoding the "black box" of NCCL/NVLink communication patterns. Autonomous Diagnostics: Transforming reactive troubleshooting into proactive cluster self-healing. Sovereign AI Infrastructure: Architecting robust foundations for the next generation of sovereign computing. Always keen to exchange insights with commercial leaders, technical peers, and strategists who are navigating the future of AI infrastructure.
Working within a large Australian financial services environment, focusing on secure enterprise platforms, technology governance, operational resilience, observability, and automation. The role involves strengthening platform reliability, security baseline, delivery quality, and engineering maturity in a highly regulated enterprise environment. This Australian enterprise experience gives me a practical view of how large organisations assess infrastructure readiness, operational risk, compliance, cost efficiency, and production-grade technology adoption. It also connects strongly with my broader focus on AI infrastructure, workload intelligence, infrastructure observability, baseline certification, and next-generation enterprise automation.
Served as the P&L owner and Head of Business for the Situational Awareness product line. Member of the Corporate Strategy Committee. Led a cross-functional team (R&D, Product, GTM) to define and execute the strategic roadmap for enterprise-grade security observability and threat detection. * Strategic Leadership & P&L Ownership: Defined the product vision and business strategy as a core member of the Security Business Strategic Committee. Successfully managed the end-to-end product lifecycle, from kernel-level R&D innovation to global market delivery. * High-Performance Traffic Analysis & Algorithms: Spearheaded the development of next-gen Network Traffic Analysis (NTA) and anomaly detection algorithms. Significantly improved detection precision and system response efficiency in high-throughput environments. * Global Expansion (GTM): Led the internationalization strategy, successfully expanding the product footprint into Southeast Asia and Europe. Established local partnerships and tailored GTM strategies to meet diverse regional compliance and operational requirements. * Enterprise-Scale Observability: Oversaw the deployment of situational awareness platforms for massive-scale enterprise environments, focusing on visibility, real-time analytics, and automated response.
Led the technological roadmap and architectural design at the Sangfor Innovation Institute. Responsible for defining the core technology stack for next-generation infrastructure security products, bridging cutting-edge research with commercial product engineering. * Architected Next-Gen Endpoint Agents (EDR): Spearheaded the technical planning and kernel-level architecture for Sangfor’s EDR (Endpoint Detection and Response) product. Relevant to AI Infra: Designed lightweight, high-performance agents for real-time monitoring and anomaly detection on host endpoints—foundational experience for building efficient infrastructure observability probes. * Full-Stack Observability Roadmap: Defined the integrated technology roadmap across EDR (Endpoint), NDR (Network), and Firewall systems. Created a unified technical framework for data collection, vulnerability detection, and threat intelligence. * Core R&D & Product Strategy: Led the requirements analysis and architectural design for critical system modules. Collaborated with core R&D teams to translate complex security requirements into scalable, high-performance technical solutions, ensuring the product's long-term competitive advantage.
A 8-year veteran leader at Trend Micro’s globally significant R&D hub. Led the Core Technology Department, bridging kernel-level engine development with massive-scale cloud data processing. Pioneered Cloud-Native Data Processing (PaaS/Big Data): Architected the cloud operations framework and big data analysis pipeline using Kubernetes (K8S), ELK Stack, and Distributed Databases. Processed massive volumes of threat telemetry, laying the foundation for modern observability architectures. Kernel-Level Engine Development: Led the R&D of core detection engines, including Probe Engines, Event Tracing, and Behavioral Analysis models. Developed low-level mechanics for ransomware detection and traffic inspection (Webshell/Tunneling). High-Performance Gateway Optimisation: Responsible for the quality and performance of enterprise-grade Mail/Web Gateways. Optimized protocol parsers (HTTP/SMTP) and system architecture to handle high-throughput, low-latency traffic loads. Global Tech Market Leadership : Led the team to achieve #1 Global Benchmark results for 4 consecutive years. Key contributor to maintaining Trend Micro’s status as the Gartner Magic Quadrant Leader in Endpoint Protection (2010-2016).
Led the design and implementation of robust testing frameworks for the company's flagship product, InterScan, ensuring high scalability and performance across multi-platform environments. Developed and executed comprehensive test strategies for security scanning technologies, focusing on multi-protocol testing, performance validation, and ensuring the highest levels of security and reliability. Architected automated test pipelines that supported continuous integration, delivering consistent test coverage across diverse platforms and environments while ensuring the product met high-performance benchmarks. Introduced and implemented agile test processes, fostering collaboration between development and testing teams to ensure timely and high-quality releases. Spearheaded the quality assurance efforts, leading performance and stress testing to identify potential bottlenecks, vulnerabilities, and optimization opportunities in the multi-protocol scanning engine. Monitored product stability through continuous regression testing, ensuring that each upgrade and iteration maintained functional integrity and improved product performance. Collaborated with cross-functional teams to ensure that user stories and requirements were thoroughly validated, providing a seamless end-to-end testing experience for both security and performance aspects of the product
Led the design and execution of cybersecurity tests for APIs and products, focusing on functionality, security vulnerabilities, and system integration across different environments. Spearheaded the development of automation tools to detect and mitigate cybersecurity threats (phishing, spam, web attacks), contributing directly to improving product security against evolving risks. Implemented end-to-end test frameworks that included performance testing, stress testing, and compatibility tests, ensuring robust product validation and stability for enterprise-grade solutions. Achieved a high test automation rate (85%) for enterprise security gateways, and a 100% automation rate for API testing using Postman tools, demonstrating my expertise in scaling quality assurance processes. Leveraged a systems-focused approach to test optimization, continuously improving automation processes and testing efficiency, enhancing both framework performance and security validation accuracy.
Research Focus: Distributed Systems Security & Confidentiality Author of "On the Confidential Auditing of Distributed Computing Systems", published in IEEE ICDCS 2004 (One of the most prestigious conferences in distributed systems). Core Research: Pioneered early frameworks for Secure Auditing and Data Privacy within large-scale distributed computing environments. The research addressed the fundamental challenge of verifying system integrity without compromising data confidentiality—a concept that is now the cornerstone of Data Sovereignty and Zero Trust architectures in modern Sovereign Clouds.
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