Kenny Sheridan | Systems / AI / Robotics
This portfolio publishes systems engineering work across accelerated infrastructure, B200, B300, AMD GPU systems, AI and machine learning systems, AI system observability, knowledge layers for AI-native and AI-ready companies, robotics-adjacent edge systems, bare metal, high performance computing, virtualization, Kubernetes, defense programs, FedRAMP and IL5 environments, and lifecycle-managed platforms.
The work spans control-plane design, host-level agents, AI system observability, AI-ready knowledge layers, virtualization, B200, B300, AMD GPU systems, hardware selection, systems integration, HPC benchmarking, AI and ML workload matching, cluster grading, validation testing, and developer tooling, with a focus on turning hardware fleets, GPU systems, pre-AI companies, and edge devices into durable operational capability.
Operating posture: connected, disconnected, defense, and edge. Commercial focus: startup to Fortune 500 scale. Systems scope: knowledge layers, observability, lifecycle, and monetization.
Control-plane code, host-level automation, Nix systems, hardware lifecycle tooling, virtualization, AI system observability, AI-ready knowledge layers, validation testing, systems integration, benchmarking, AI and ML workload matching, customer-specific infrastructure products, and libraries behind accelerated infrastructure, defense, edge, and high-assurance systems delivery.
Review the resume, browse public Codeberg repositories, or use Forgejo for the fuller private code forge covering systems architecture, AI system observability, and AI-ready knowledge-layer design.