AI Architect Practice Arena
AI System Design
Design an LLM inference serving platform at scale
Design a retrieval-augmented generation (RAG) platform at scale
Design an agent orchestration platform with real tool use
Design a feature store / fine-tuning data pipeline
Design a content moderation and safety system for generated content
Design a multimodal search / recommendation system
Design an LLM evaluation and observability platform
Design a fine-tuning / RLHF training pipeline at scale
Design a multi-tenant AI platform
Design a sandboxing architecture for AI agent code execution
Design an on-device / edge AI inference architecture
Design a training-data provenance and IP-risk architecture
Design durable execution for long-running AI agents
Design a ChatGPT-style conversational service
Design an AI coding assistant (Copilot-style)
Design an LLM-powered customer support assistant
Design LLM application security against prompt injection
Design an AI data flywheel and human-feedback platform
Design a model release, canary, and rollback platform
Design persistent AI memory and personalization
Design a real-time voice AI assistant
Design enterprise PDF Q&A with page citations and grounding
Design enterprise hybrid retrieval with access-aware ranking
Design identity and access management for AI agents and MCP tools
Design a real-time fraud and risk decisioning system
mlops-llmops
Design a model and experiment registry with promotion gates
Design a training–serving skew detection and prevention platform
Design data/concept drift monitoring and shadow scoring
Design a batch and online unified prediction platform
Design ML CI/CD and continuous training pipelines
fde-deployment
Why Forward Deployed Engineer — not pure SWE or pure Architect
Ambiguous customer decomposition (Palantir-style case)
Customer discovery to production MVP wedge
Client simulation — pushback, bad news, and unblock
Production AI deep-dive — evals, cost, guardrails, take-home defense
Enterprise discovery call — "VP wants a chatbot"
Enterprise deploy — VPC, SSO, hosted vs self-hosted AI
Practical FDE coding — production-shaped drills
Cloud Architecture
Design a GPU capacity-planning and procurement system
Design a multi-region strategy for training vs. serving
Design disaster recovery for a model-serving platform
Design the network architecture for distributed training
Design the security and compliance architecture for an AI system
Design container orchestration and cost optimization for AI workloads
Design an enterprise LLM gateway with semantic cache — gateway vs sidecar; cache-in-process vs cache-as-service
Design a foundation-model pretraining cluster
Design an enterprise AI landing zone
Design GenAI FinOps, chargeback, and quotas
Design private connectivity and egress control for AI
General System Design
Design a distributed rate limiter
Design a real-time chat/messaging system at scale
Design a news feed / ranking system
Design a distributed job scheduler / task queue
Design a distributed unique ID generator
Design a collaborative document editing system
Design a distributed cache / global content delivery layer
Design a notification system
Design a URL shortener
Design a video streaming platform
Design a web crawler
Design search autocomplete / typeahead
Design a ride-sharing service (Uber-style)
Design a payment processing system
Design a distributed file storage system (Dropbox/Drive-style)
Design a distributed key-value store
Design a metrics and monitoring system
Design an event-driven architecture with Kafka
Behavioral
Staffing reduction from 10 to 2 in a supply chain workflow
Finding and fixing a real FinOps gap in my own org
Finding and fixing unauthenticated endpoints across six repos
Payments and supply chain modernization at Lucid Motors
Leading a 0-to-1 AI product build under real ambiguity
Influencing a technical decision without authority
A technical bet that did not pay off
Navigating deep technical disagreement with peers
Mentoring and growing engineers toward the next level
Scalability & Governance Trade-offs
Cost vs. latency vs. safety — a reasoning framework
Build vs. buy (or embed) for shared services
Centralize vs. federate governance
Build vs. train-from-scratch vs. fine-tune: foundation model strategy
coding
Staff+ coding bar — how this round is graded
Implement an LRU cache (Staff+ concurrency extension)
Implement a token-bucket rate limiter (in-process)
Time-based key-value store
Concurrent bounded blocking queue
Top-K frequent elements (stream-aware)
Merge K sorted lists / iterators
Clone a graph (cycle-safe)
Debug: broken cache eviction
Design an in-memory pub/sub (LLD in code)
Prefix-sum subarray patterns (Staff+ follow-ups)
Implement consistent hashing with virtual nodes
Design an elevator system (LLD / machine coding)
Design a parking lot (LLD / machine coding)
Implement a Trie / prefix tree (Staff+ autocomplete extension)
Find median from a data stream (Staff+ concurrent extension)
Serialize and deserialize a binary tree (Staff+ schema extension)
Design a hit counter (Staff+ distributed extension)
Implement a circuit breaker (Staff+ resilience extension)
Implement an idempotent event consumer
staff-plus-interview-craft
What Staff+ actually signals in interviews
Questions you should ask in a Staff+ interview
What not to waste time on in Staff+ interviews
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