Platform Performance & Resilience (AI-Enabled) Engineer

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.

• 5 + years of software engineering experience with a focus on distributed systems.
• Proven experience in performance engineering and scalability architecture.
• Hands-on experience with k6 or similar performance testing tools.
• Experience designing and executing load, stress, and scalability tests.
• Strong background in capacity planning and infrastructure sizing.
• Experience working directly with customers on performance and system behavior.
• Deep understanding of distributed systems patterns: concurrency control, latency management, retries/backoff, circuit breakers.
• Experience with cloud-native systems (AWS, GCP, or Azure) and Kubernetes.
• Strong debugging and performance analysis skills.

• Experience with multi-tier architectures (edge, on-prem/store, cloud).
• Experience building simulation or virtualization environments.
• Familiarity with event-driven systems such as Kafka, Pub/Sub, or MQ.
• Experience implementing observability frameworks (OpenTelemetry, Grafana, ELK).
• Exposure to AI-driven testing or validation systems.

Toshiba Global Commerce Solutions is a dynamic billion-dollar global company based in Research Triangle Park, NC, providing retail store solutions to your favorite brands. Have you ever been in a hurry and made use of the self-checkout at Lowe's Foods, earned fuel rewards at Kroger, or just paid for purchases at retailers such as Walmart, Michaels, Carrefour, The Gap, Calvin Klein, Boots, Cencosud, BJ's, or Costco? These are just a few examples of our in-store solutions and impressive customer base that made us the world's installed market share leader.

The nature of retail is changing quickly, so if you share our 'Together Commerce' vision of a seamless two-way, participatory shopping experience, let's get together to drive the new economy.

Toshiba Global Commerce Solutions, Inc. offers a competitive salary and generous benefits package including the following:

• Group health coverage (medical, dental, & vision)
• Employee Assistance Programs
• Pre-tax spending accounts
• 401(k) plan (with company match)
• Company provided life insurance
• Pet Insurance
• Employee discounts
• Generous paid holiday schedule, paid vacation & sick/personal days

• 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.

• 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.

• 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.

• Own infrastructure sizing models used in customer Statements of Work (SOWs).
• Provide validated recommendations for cluster sizing, database capacity, message throughput, and resource allocation.

• Define system behavior under failures, degraded dependencies, and partial outages.
• Establish patterns such as timeouts, retries, circuit breakers, graceful degradation, and workload isolation.

• Ensure end-to-end transaction visibility across edge, store, and cloud.
• Define telemetry requirements to quickly identify performance bottlenecks.
• Improve signal quality for performance and reliability diagnostics.

• Use AI-driven systems to generate and evaluate performance and resilience scenarios.
• Improve detection of regressions and anomalies in large-scale test runs.
• Automate validation workflows to enhance production readiness.