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
9 years of employment as a software developer
Bachelor's degree, Electrical, Electronics and Communications Engineering, Rank: 8/191(5%), Bachelor's degree, Electrical, Electronics and Communications Engineering, Rank: 8/191(5%) at National Taiwan University
Computer Science, Computer Science at Coursera
Master's degree, Electrical, Electronics and Communications Engineering, GPA: 4.015, Master's degree, Electrical, Electronics and Communications Engineering, GPA: 4.015 at Stanford University
English, Chinese, Mandarin