Cloud & AI Platform, Senior Cloud Solution Architect
North Carolina, United States
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Summary
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Rockstar
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Top School
Larry Wall is a seasoned Cloud & AI Platform Senior Cloud Solution Architect with 38 years of engineering experience, based in North Carolina and currently shaping cloud-native and AI solutions at Microsoft. He specializes in Azure PaaS, AKS, microservices and platform architectures, combining deep systems knowledge with pragmatic guidance for product and ISV partners. A long-term Microsoft practitioner, he has evolved from customer engineering and consulting into senior cloud architecture roles, driving adoption of scalable, production-ready platforms. Outside cloud practice, he is an active low-level open-source contributor to the Raku ecosystem—improving the Rakudo compiler, MoarVM VM, and NQP—highlighting a rare blend of systems-level language/runtime optimization and cloud architecture expertise. That mix of compiler-level performance work and cloud platform design gives him a practical edge in performance-sensitive, distributed systems and language/runtime-aware tooling.
38 years of coding experience
20 years of employment as a software developer
Bachelor of Electrical Engineering, Electronics, Bachelor of Electrical Engineering, Electronics at University of North Carolina at Charlotte
Contributions:962 commits, 555 pushes, 8 branches in 10 years 4 months
Contributions summary:Larry made numerous contributions focused on improving the Raku compiler (Rakudo). Their work involved implementing and optimizing core functionalities, especially in the `List.pm` and `Any.pm` modules. This included improvements to existing routines like `combinations` and `permutations`, refactoring methods, and addressing performance issues within the compiler. The user was involved in optimizing various operations, ensuring the code's efficiency.
Contributions:170 commits, 77 pushes, 2 branches in 3 years 6 months
Contributions summary:Larry made multiple contributions focused on enhancing the functionality of the NQP (Not Quite Perl) language. They added several new opcodes for unicode properties and hooked them up, demonstrating work on language features. Further work included refactoring code to reduce the bit size used by some internal variables. These efforts were related to regex engine and involved code in both NQP itself, and in related runtime and compilation files.
rakunqp
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Larry Wall - Cloud & AI Platform, Senior Cloud Solution Architect