toshibaglobalcommercesolutions · Durham, NC
Skills: AWS, Docker
Toshiba Global Commerce Solutions is seeking a Platform Performance & Resilience (AI‑Enabled) Engineer that is a hands-on architecture role responsible for leading performance, scalability, and resilience engineering across a distributed platform spanning edge devices, in‑store servers, and cloud services. Sitting at the intersection of customer delivery, platform architecture, and production engineering, this role engages directly with customers and internal teams to define performance expectations, validate real‑world system behavior, drive performance testing strategies, and leverage AI to scale non-functional validation across the platform. Note: Toshiba Global Commerce Solutions will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work in the United States without a need for current or future visa sponsorship . Must be located near or within the Raleigh-Durham area. Responsibilities Customer-Facing Performance & Scalability Engineering Engage directly with customers to define performance expectations, scale targets, and operational constraints. Translate business requirements into concrete performance models and test plans. Provide guidance on system behavior under peak loads, store concurrency, and transaction volume. Performance Testing Strategy (k6 and Beyond) Define and lead platform-wide performance testing using k6. Design realistic load models reflecting POS behavior, store concurrency, and cloud interactions. Ensure repeatable, automated performance validation integrated into delivery pipelines. Virtualization & Simulation of Performance Environments Lead the design of virtualized environments simulating production-scale behavior. Build and evolve simulators for store workloads, transaction flows, and external dependencies. Enable testing at scale without requiring full production infrastructure. Infrastructure Sizing & Capacity Modeling Own …t…
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