My first instinct was to treat this like a toy problem and just sketch out some classes.
Start by clarifying the scope: is this a simple local game, a networked multiplayer game, or a scalable service? Then design the core game logic, state management, and APIs, and discuss trade-offs for scalability, latency, and fault tolerance. Finally, consider how to leverage NVIDIA's strengths in accelerated computing for AI opponents or high-performance simulations.
Pro tip: Emphasize that even a simple game like rock-paper-scissors can be a vehicle to discuss distributed systems, concurrency, and AI—showing you can think beyond the basics. Also, proactively mention how you'd test and monitor the system, as reliability is crucial at NVIDIA.
Ask questions to determine if the game is single-player vs AI, multiplayer networked, or a massively scalable service. Clarify expected load, latency requirements, and whether persistence or leaderboards are needed.
Define the rules, move representations, and outcome determination. Outline the data model for games, players, and moves, and decide on stateless vs stateful components.
Propose a high-level architecture: client, API gateway, game service, matchmaking, and storage. Define key APIs for creating games, submitting moves, and retrieving results.
Discuss how to handle concurrent games, ensure consistency (e.g., using optimistic locking or queues), and scale horizontally. Consider replication, sharding, and handling failures gracefully.
Compare design choices (e.g., WebSockets vs polling, SQL vs NoSQL) and highlight how NVIDIA GPUs could accelerate AI opponents or large-scale simulations. Mention monitoring, logging, and testing strategies.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.