Demonstrate strong practical knowledge of a backend programming language such as JavaScript with Node dot js, Python, Java, Go, or similar. Cover language fundamentals, idiomatic usage, standard library features, package and dependency management, common frameworks and ecosystem tools, testing strategies and tooling, error handling and observability, and patterns for maintainable server side code. Be ready to explain concurrency and asynchronous models in the language, performance considerations, security best practices, deployment and packaging approaches, and examples of backend services or APIs you built including trade offs and chosen libraries.
EasyTechnical
0 practiced
Define concurrency and parallelism and provide concrete examples in Python, Go, and Java where code is concurrent but not parallel, and where code runs in parallel. As an AI Engineer, explain the implications for model training, CPU-bound preprocessing, and serving architectures.
HardSystem Design
0 practiced
Design a robust training data ingestion pipeline that handles high-throughput sources, guarantees deduplication, performs schema validation, supports idempotent writes, and applies backpressure to downstream preprocessors or storage. Describe key components, data formatting choices, stateful vs stateless processing, and recovery techniques for partial failures.
HardTechnical
0 practiced
You have a CPU-bound Python inference component and are asked to port it to Go or Java to increase throughput. Outline a robust migration plan covering profiling to identify hotspots, selecting kernels to rewrite, building interoperable interfaces (gRPC/REST) during migration, ensuring numerical parity, testing strategies, and a rollout plan with rollback capabilities.
HardTechnical
0 practiced
Your service spends significant time serializing and deserializing images and tensors for each request. Propose concrete optimizations to reduce overhead, including zero-copy approaches, binary framing protocols, efficient buffer reuse or pooling, using shared memory for intra-host transfers, and trade-offs when moving to RDMA or low-level networking for inter-host transfers.
MediumSystem Design
0 practiced
Design a low-latency model serving API that must handle 100 requests per second with a 50ms P95 latency SLO. Define the API contract, choice between synchronous and asynchronous models, batching strategy, concurrency model, hardware assumptions (CPU/GPU), caching, monitoring, and graceful degradation strategies. Justify your choices as an AI backend engineer.
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