Summary
Yu-cheng Liang is a Senior Staff SRE and Security Architect with 10+ years designing large-scale identity and access management systems across Google, Uber, and NVIDIA, where he now leads AI agent identity strategy. He blends deep IAM engineering—ACL recommenders, privileged access platforms, and lateral-movement mitigations—with applied AI/ML and LLMs to automate access decisions and discover risky access paths at scale. At NVIDIA he architected a platform-agnostic hybrid/federated model for non-human identities that aligns with emerging ODIS and NIST efforts, while at Uber and Google he built production AI-driven approval and recommender systems that measurably improved least-privilege adoption. His background ranges from low-level authentication and SMB protocols to cloud-native JIT PAM, giving him a rare full-stack security perspective. Based in Sunnyvale, he complements his industry work with personal ML projects—GANs, image captioning, and recommender prototypes—demonstrating continual hands-on experimentation beyond corporate initiatives.
10 years of coding experience
13 years of employment as a software developer
Bachelor's degree, Electrical, Electronics and Communications Engineering, Bachelor's degree, Electrical, Electronics and Communications Engineering at National Taiwan University
Computer Science, Computer Science at Coursera
Master's degree, Electrical, Electronics and Communications Engineering, Master's degree, Electrical, Electronics and Communications Engineering at Stanford University
English, Chinese, Mandarin