Evaluate system design skills: scalability, trade-offs, and architecture decisions.
Evaluates the candidate's ability to clarify ambiguous requirements and define system scope before designing.
Candidate asks targeted questions about scale, consistency requirements, latency expectations, and user patterns. They scope the problem to a manageable size and explicitly state assumptions.
Candidate starts drawing boxes without understanding what they're building, makes assumptions without stating them, or cannot distinguish between must-have and nice-to-have requirements.
Assesses the ability to design a coherent system architecture with well-defined components and clear data flow.
Candidate draws a clear architecture diagram with well-defined components (API gateway, services, cache, database, queue). Data flow is logical, and each component has a clear responsibility.
Architecture is a random collection of boxes with no clear data flow, candidate cannot explain why components exist, or the design is either over-engineered or overly simplistic for the requirements.
Evaluates choices around data modeling, database selection, and storage patterns.
Candidate designs a clear data model, selects appropriate databases with justification (SQL for relational data, Redis for caching, Elasticsearch for search), and discusses indexing, partitioning, and replication strategies.
Candidate uses a single database for everything without justification, cannot define a basic data model, or ignores data access patterns when choosing storage.
Assesses understanding of horizontal scaling, caching, load balancing, and performance optimization.
Candidate identifies bottlenecks proactively, proposes specific solutions (horizontal scaling, read replicas, CDN, cache layers), and discusses trade-offs of each approach including cache invalidation strategies.
Candidate says 'just add more servers' without specifics, doesn't identify bottlenecks, or proposes solutions that introduce new problems without acknowledging them.
Evaluates the candidate's ability to articulate trade-offs and make justified design decisions.
Candidate discusses CAP theorem implications, consistency vs. availability trade-offs, cost vs. performance, and build vs. buy decisions. They justify choices with reasoning, not dogma.
Candidate insists there are no trade-offs, cannot compare alternatives, or makes every decision based on 'that's what we used at my last job' without analysis.
Assesses whether the candidate designs for failure and considers system reliability.
Candidate proactively discusses failure modes, circuit breakers, retries with backoff, dead letter queues, and graceful degradation. They design for failure, not just the happy path.
Candidate assumes nothing will fail, has no strategy for handling partial outages, or doesn't consider what happens when dependencies are unavailable.
Interview notes go here...
Design and implement server-side logic, APIs, and database integrations.
Lead and grow an engineering team while driving execution on product roadmap and technical strategy.
Work across the entire stack — frontend UI, backend APIs, and database layer.