For reinforcement learning training pipelines where AI-generated code is evaluated in sandboxes across potentially untrusted workers, the threat model is both the code and the worker. You need isolation in both directions, which pushes toward microVMs or gVisor with defense-in-depth layering.
As the founding member of the backend team, I worked to establish the underlying technical architecture that powers the persistent live components of the game. As the backend team grew, we built numerous C# microservices running in Kubernetes hosted on Azure. Viewing this as a long-term live-service game, we designed our systems with that in mind. Multiple region-aware matchmaking flows. An internal web portal for customer support. Player reporting and moderation systems. Cross-platform account linking. Login queues. Extensive load testing. The list goes on and on.
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