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).
System Design and Scalability
Covers architectural thinking and design tradeoffs for building reliable, high performance systems. Topics include design decision reasoning given constraints such as cost, latency and availability; scaling strategies including horizontal and vertical scaling, load balancing, caching patterns, database partitioning and sharding, read replicas, and asynchronous processing; capacity planning and observability; spotting and explaining bottlenecks such as hot partitions, single points of failure, database locks and network limits; and communicating technical impact in business terms. Candidates should be able to justify choices, compare alternatives, and articulate metrics and monitoring approaches to validate design decisions.
Company Specific Technology Knowledge
Deep knowledge of the specific company's technology stack, engineering architecture, platform components, and major technical challenges. This includes familiarity with the languages, frameworks, cloud providers, orchestration and infrastructure tools, internal platforms, common performance and scalability concerns, and recent engineering initiatives or launches. Interviewers probe this area to evaluate whether a candidate understands the precise technical environment they would join, can speak to tradeoffs in architecture and tooling, and can explain how their own technical skills map to the company specific needs.
System Architecture and Tradeoffs
Ability to decompose complex systems into components and define clear responsibilities, interfaces, and interactions. Evaluate architectural alternatives and articulate core trade offs such as consistency versus availability, latency versus throughput, simplicity versus extensibility, and cost versus performance. Explain how design choices affect scalability, resilience, failure modes, and operational burden, and justify architecture decisions based on expected load patterns and business requirements.
Distributed Systems and Scalability
Conceptual understanding of distributed systems and patterns for scaling large consumer platforms. Topics include consistency and availability trade offs, partition tolerance, replication and sharding, caching strategies, eventual consistency models, consensus and failure recovery patterns, load balancing and capacity planning, real time and batch processing design, and observability and performance trade offs when designing for scale.
Decision Making Under Uncertainty
Focuses on frameworks, heuristics, and judgment used to make timely, defensible choices when information is incomplete, conflicting, or evolving. Topics include diagnosing unknowns, defining decision criteria, weighing probabilities and impacts, expected value and cost benefit thinking, setting contingency and rollback triggers, risk tolerance and mitigation, and communicating uncertainty to stakeholders. This area also covers when to prototype or run experiments versus making an operational decision, how to escalate appropriately, trade off analysis under time pressure, and the ways senior candidates incorporate strategic considerations and organizational constraints into choices.