Build a distributed in-memory data store in Rust for AWS's serverless big-data/AI storage platform

This SDE II role on AWS Serverless Storage builds core features of a distributed in-memory data store using Rust, focused on high-throughput data processing for big data analytics and AI workloads. You'll also build high-availability microservices to manage cluster lifecycle on EC2/ECS/EKS with dynamic scaling and safe rollouts. Requires 3+ years professional software development, 2+ years design/architecture experience, and hands-on experience with C#/C++/Java/Perl or similar for large-scale multi-tiered/multi-threaded systems.

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Likely format

Likely includes an online coding assessment plus behavioral rounds structured around Amazon's Leadership Principles, consistent with standard Amazon SDE II hiring loops.

What this interview tests

Distributed in-memory data store design (Rust: memory safety, concurrency)
High-throughput data processing for big data / AI workloads
Cluster lifecycle microservices on EC2/ECS/EKS: scaling, safe rollout
Node-level performance optimization (CPU/memory/disk)
API design for flexible, scalable data-persistence layers
Integration with big-data ecosystem (e.g., Spark)

Common question themes

Design a distributed in-memory data store handling high-volume datasets

Rust concurrency/memory-safety concepts, or equivalent discipline in another systems language

Design a cluster-lifecycle control service with safe rolling updates on EC2/ECS/EKS

A time you optimized CPU/memory/disk utilization at the node level

Object-oriented / multi-threaded system design for a large-scale distributed application

End-to-end ownership of the SDLC for a service you built

How candidates describe it

Real Software Development Engineer II interview stories — retold from candidates' public write-ups, with sources.

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Interviewed March 2022 · Not specified

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