Siamak Amirghodsi

The next competitive divide will not be between companies that modernize their operating models and those that don’t. It will be between organizations that fundamentally redesign how they operate around data, intelligent systems, and real-time, autonomous decision-making—and those that layer AI onto legacy structures. My career has centered on helping enterprise leaders navigate exactly that transformation. I’m a globally recognized technology executive with more than 20 years of experience building and scaling AI, data platforms and high-performance computing systems inside complex, regulated enterprises. I’ve led large-scale initiatives spanning 400+ cross-functional stakeholders and $500B to $1B+ budgets, including the architecture of trading, risk, and data platforms for GSIBs, major banks, and leading hedge funds. After years of leading enterprise transformation initiatives, I made an intentional move into deeply hands-on roles at AWS and Google to work directly on cloud infrastructure, large-scale distributed systems, advanced analytics, and next-generation, cloud-native data & AI architectures. I went from teaching an AI model to say "good morning" to helping architect enterprise-critical platforms that improve how institutions assess risk, allocate capital, accelerate decision-making, and create transparency under intense regulatory scrutiny. That experience prepared me for my next chapter: helping midmarket and enterprise companies transition from traditional operating models to modern, data-fluent organizations that prioritize the ethical use of AI to change how we do business. My expertise spans advanced analytics at scale, cloud-native and HPC platforms, [Quantum Computing], regulatory and quantitative risk systems, enterprise governance and infrastructure strategy, and open-source and distributed computing architectures. I’m a