Systems Architecture & Distributed Systems Topics
Large-scale distributed system design, service architecture, microservices patterns, global distribution strategies, scalability, and fault tolerance at the service/application layer. Covers microservices decomposition, caching strategies, API design, eventual consistency, multi-region systems, and architectural resilience patterns. Excludes storage and database optimization (see Database Engineering & Data Systems), data pipeline infrastructure (see Data Engineering & Analytics Infrastructure), and infrastructure platform design (see Cloud & Infrastructure).
Full Stack Architecture and Feature Design
Ability to design complete features considering frontend UX, backend API design, database schema, and data flow. Understanding of separation of concerns and communication between layers. API-first design thinking. Discussing trade-offs (e.g., complex queries on backend vs post-processing on frontend). Designing for extensibility and maintainability.
System Architecture Communication and Documentation
Assess the candidate ability to describe, document, and communicate system architecture both visually and verbally. Candidates should present what a system does and who uses it, identify major components and how they interact, show data flow and integration points, and explain critical architectural decisions and trade offs. Interviewers expect clear diagrams using standard conventions that show high level views, component interactions, and deployment topology, accompanied by concise narrative documentation. Strong answers include multiple views tailored to the audience, labeled diagrams, and justification of design choices while avoiding unnecessary implementation detail. Candidates should be able to discuss scaling strategies, reliability and operational considerations including failure modes, migration paths, observability, and deployment considerations. The scope includes common architectural building blocks such as microservices, application programming interfaces, databases, caching layers, and message buses, as well as consistency and availability implications and service to service communication patterns, and the connection between technical choices and business context.
Technical Product Challenges
Test the candidate knowledge of a company product portfolio and the technical challenges that arise from those products. This includes product architecture and integration points, scaling and performance bottlenecks, reliability and availability trade offs, technical debt and legacy constraints, data and infrastructure considerations, security implications, and how engineering and product teams prioritize technical investments. Candidates should demonstrate specific examples of likely technical problems for the company product type, explain potential mitigation strategies, and connect their past experience to how they would address similar challenges.
Network Architecture and Communication Patterns
Design and analysis of network architectures and service communication patterns for reliable, performant, and secure distributed systems. Topics include network topology and capacity planning, load balancing strategies, content delivery networks, caching and edge delivery, application programming interface gateway design, service to service communication patterns including synchronous and asynchronous messaging, message queues, publish subscribe, request routing, retries and backoff, timeouts, idempotency, circuit breakers, bulkheads, and service mesh considerations. Also covers latency optimization, failure modes and resilience, observability and monitoring, network security principles such as encryption and segmentation, and how architectural choices affect scalability and operational complexity.
CAP Theorem and Consistency Models
Understand the CAP theorem and how Consistency, Availability, and Partition Tolerance interact in distributed systems. Know different consistency models including strong consistency such as linearizability, eventual consistency, causal consistency, and session consistency, and how to apply them to different use cases. Be familiar with consensus protocols and distributed coordination primitives such as Raft and Paxos, quorum reads and writes, two phase commit and when to use them. Understand trade offs between consistency and availability under network partitions, patterns for hybrid approaches where different data uses different guarantees, and the product and developer experience implications such as latency, stale reads, and API contract clarity.
Caching Strategies and Patterns
Comprehensive knowledge of caching principles, architectures, patterns, and operational practices used to improve latency, throughput, and scalability. Covers multi level caching across browser or client, edge content delivery networks, application in memory caches, dedicated distributed caches such as Redis and Memcached, and database or query caches. Includes cache design and selection of technologies, defining cache boundaries to match access patterns, and deciding when caching is appropriate such as read heavy workloads or expensive computations versus when it is harmful such as highly write heavy or rapidly changing data. Candidates should understand and compare cache patterns including cache aside, read through, write through, write behind, lazy loading, proactive refresh, and prepopulation. Invalidation and freshness strategies include time to live based expiration, explicit eviction and purge, versioned keys, event driven or messaging based invalidation, background refresh, and cache warming. Discuss consistency and correctness trade offs such as stale reads, race conditions, eventual consistency versus strong consistency, and tactics to maintain correctness including invalidate on write, versioning, conditional updates, and careful ordering of writes. Operational concerns include eviction policies such as least recently used and least frequently used, hot key mitigation, partitioning and sharding of cache data, replication, cache stampede prevention techniques such as request coalescing and locking, fallback to origin and graceful degradation, monitoring and metrics such as hit ratio, eviction rates, and tail latency, alerting and instrumentation, and failure and recovery strategies. At senior levels interviewers may probe distributed cache design, cross layer consistency trade offs, global versus regional content delivery choices, measuring end to end impact on user facing latency and backend load, incident handling, rollbacks and migrations, and operational runbooks.
Technical Innovation and Modernization
Covers leading and executing technical change that raises the engineering bar while preserving operational stability. Topics include identifying and prioritizing innovation opportunities, sponsoring research and experimentation, running proofs of concept and pilots, and introducing new tools or frameworks. Also includes strategies for modernizing legacy systems and architecture with minimal business disruption, managing technical debt, migration planning, rollback and cutover approaches, and maintaining reliability and continuity. Evaluated skills include optimizing performance and cost at scale, establishing engineering standards and best practices, governance and risk management, stakeholder alignment and communication, measuring impact and return on investment, and balancing long term innovation with short term pragmatism.
Trade Off Analysis and Decision Frameworks
Covers the practice of structured trade off evaluation and repeatable decision processes across product and technical domains. Topics include enumerating alternatives, defining evaluation criteria such as cost risk time to market and user impact, building scoring matrices and weighted models, running sensitivity or scenario analysis, documenting assumptions, surfacing constraints, and communicating clear recommendations with mitigation plans. Interviewers will assess the candidate's ability to justify choices logically, quantify impacts when possible, and explain governance or escalation mechanisms used to make consistent decisions.
Technical Project Stories
Prepare two to four hands on technical project narratives that demonstrate engineering depth, architectural thinking, and measurable outcomes. For each project describe the business problem, system architecture or design choices, trade offs evaluated, scaling and reliability challenges, instrumentation or observability decisions, implementation details and technologies used, your specific responsibilities, and the measurable results achieved. Be prepared to dive deep on technical decisions, show diagrams or component flows if asked, describe how technical debt and operational run book items were managed, and explain how the work influenced broader engineering practices. Include examples across front end, back end, infrastructure, data, and security as relevant to the role.