Interview Prep — Question Index

This page consolidates every Common Interview Questions block across the site into a single rapid-recall index. Each link below jumps to a page that ends with a <details> Q&A section covering the topic. Use this when prepping for a phone screen, a system design round, or a recruiter call where you need to brush up on a specific service or pattern in minutes rather than hours.

Pages are grouped topically — LLM Engineering and ML foundations first, then the data platforms (Databricks, Snowflake), followed by AWS service families (AI/ML, Compute, Security, Database, Serverless), and finally end-to-end System Design.

1. AI / ML — LLM Engineering

Modern LLM-app patterns: retrieval, agents, evaluation, serving, and the surrounding tooling for production RAG systems.

Agents and MCPagentsagent loops, tool use, Model Context Protocol Function Calling and Structured OutputagentsJSON schema, tool routing, validation Hybrid Search and RerankingretrievalBM25 + dense fusion, cross-encoder rerank LangGraph and DSPyagentsstate machines, prompt compilation, optimizers RAG Evaluation with RAGASretrievalfaithfulness, context precision, answer relevance vLLM and QuantizationproductionPagedAttention, GPTQ, AWQ, throughput tuning How Vector Embeddings Work in RAGragembedding models, similarity, chunking strategy RAG from Scratchragingest pipeline, retrieval, prompt assembly Weaviate Vector DatabasevectorHNSW, hybrid filters, schema design MyDocumentIntelligence Architectureprojectsend-to-end RAG product, doc ingest, scaling

2. AI / ML — Foundations

Classical deep-learning building blocks that still come up in screens for ML roles.

LSTM Networkslstmgates, vanishing gradients, vs. Neural Network Sentiment Classifierdeep learningembeddings, loss, training loop

3. Databricks

Lakehouse architecture, Delta Lake internals, PySpark performance, and Mosaic AI.

Bronze Layermedallion architectureraw ingest, Auto Loader, schema evolution Silver Layermedallion architecturecleansing, conformed dimensions, SCD Gold Layermedallion architectureaggregations, BI marts, semantic models Delta Live Tablesdelta lakedeclarative pipelines, expectations, CDC Mosaic AI Vector Searchmosaic aimanaged embeddings, sync indexes, hybrid query Liquid Clusteringperformancevs. Performance OptimizationperformanceAQE, broadcast joins, file sizing, caching PySpark Deep DivefundamentalsCatalyst, Tungsten, RDD vs. PySpark Data Cleaningdata prepnull handling, dedup, type coercion Databricks Asset BundlestoolsCI/CD, env promotion, bundle config Unity Catalog Setupunity catalogmetastore, lineage, fine-grained access control

4. Snowflake

Snowflake-specific architecture, performance, and governance topics. (No standalone Snowflake pages currently carry the Q&A block — see Databricks for cross-platform lakehouse questions.)

5. AWS — AI / ML

Managed AI services for vision, language, and document understanding.

AWS AI Services OverviewSectionservice map, when to use which, pricing models Amazon Comprehendai servicesNER, sentiment, custom classifiers, PII redaction Amazon Rekognitionai servicesimage/video labels, face match, content moderation Amazon Textractai servicesOCR, forms, tables, async vs sync API

6. AWS — Compute / Storage / Networking

Core infrastructure primitives behind almost every AWS system-design answer.

Amazon EC2computeinstance families, Spot vs On-Demand, ENI limits, EBS Auto Scaling EC2 and EMRcomputetarget tracking, lifecycle hooks, warm pools AWS EMRcomputecluster types, Spot fleet, EMR on EKS ECS, EKS, and Fargatecomputeorchestration trade-offs, task vs pod, networking modes Amazon S3storagestorage classes, consistency, lifecycle, encryption S3 Transfer AccelerationstorageCloudFront edges, multipart, when worth it Amazon VPCnetworkingsubnets, NAT, peering, Transit Gateway, endpoints Amazon CloudFrontnetworkingcache behaviors, signed URLs, origin failover API GatewaynetworkingREST vs HTTP vs WebSocket, throttling, usage plans Route 53networkingrouting policies, health checks, failover, alias records

7. AWS — Security / Monitoring

Identity, secrets, audit, and observability primitives that frequently anchor a security-focused interview round.

IAMidentity secretspolicies, roles, trust, condition keys, least privilege KMSidentity secretsCMK vs data keys, envelope encryption, grants Secrets Manageridentity secretsrotation, vs Parameter Store, cross-account access CloudTraildetectionmgmt vs data events, multi-region trails, integrity AWS Config and Inspectordetectionrules, remediation, vuln scanning CloudWatchmonitoringmetrics, logs, alarms, composite alarms CloudWatch Events / EventBridgemonitoringrules, schedules, cross-account buses CloudFormationmonitoringstacks, drift, change sets, nested templates

8. AWS — Database / Analytics / Serverless

Managed data stores, ETL/analytics, and event-driven compute — the backbone of most data-engineering rounds.

Amazon RDSdatabaseengines, Multi-AZ vs read replicas, backups Amazon Auroradatabasestorage layer, Global Database, Serverless v2 Amazon DynamoDBdatabasepartition keys, GSIs, streams, on-demand vs provisioned Amazon ElastiCachedatabaseRedis vs Memcached, cluster mode, eviction Amazon Athenaanalyticspartitioning, Iceberg, workgroups, cost control Amazon QuickSightanalyticsSPICE, RLS, embedded analytics AWS Glue Data Cataloganalyticscrawlers, schema discovery, Lake Formation AWS Glue ETL ServiceanalyticsDynamicFrames, job bookmarks, workers AWS Glue Workflowanalyticstriggers, blueprints, orchestration Kinesis Data Firehoseanalyticsbuffering, dynamic partitioning, transforms Lambdaserverlesscold starts, concurrency, layers, provisioned Step FunctionsserverlessStandard vs Express, retry/catch, callback patterns Kinesis Data Streamsserverlessshards, KCL, enhanced fan-out, ordering

9. System Design

End-to-end AI system design questions — the kind that show up in senior staff and architect interviews.

System Design Q&A blocks live on AI Systems pages — see the Design / AI Systems index for the full set of architecture diagrams (Sequence, ERD, DFD) covering the same systems.

10. How to Use This Index

Tip

To rehearse a topic: open the linked page, scroll to the Common Interview Questions block at the bottom, and click the <details> summaries to reveal answers one at a time. Each page also has a Table of Contents at the top for the full content, so you can review the underlying material first and then test recall against the Q&A block.