Design & User Experience Topics
User experience design, frontend architecture, and design systems. Includes UX principles, accessibility, and design documentation.
Technical Search Engine Optimization
Comprehensive coverage of technical search engine optimization for web products, including diagnosis, auditing, remediation, and ongoing monitoring of issues that affect crawling, indexing, and organic ranking. Core areas include crawlability and indexation, site architecture and URL structure, internal linking and XML sitemap hygiene, robots.txt and meta robots configuration, canonicalization strategies, redirect management including redirect chains and loops, server response codes and error handling, duplicate content detection and remediation, hreflang and internationalization, and crawl budget considerations. Performance and user experience topics include page speed optimization and Core Web Vitals such as Largest Contentful Paint, First Input Delay, and Cumulative Layout Shift, mobile usability and mobile first indexing, HTTPS implementation and mixed content resolution, structured data markup and schema validation, and techniques such as caching, content delivery networks, image optimization, critical CSS, deferred JavaScript, and server side rendering to improve performance. Candidates should be able to perform full technical audits, use and interpret results from industry tools and platforms, triage and prioritize findings by business impact and implementation effort, produce clear audit reports and remediation plans, translate findings into engineering action items, coordinate fixes with product and engineering teams, verify fixes through testing and monitoring, and establish ongoing site health monitoring and automation.
Technical Depth & Areas of Specialization
Every strong candidate has one or more areas of technical depth that go beyond generalist knowledge. Discuss the area(s) where you have the most depth: how you identify it (a subsystem, technology, domain, or class of problem you gravitate toward), a concrete project or accomplishment that demonstrates that depth, how you actively keep that expertise current (reading, communities, side projects, postmortems), and how that depth changes the way you make trade-offs or collaborate with generalists on your team. Areas of specialization are highly individual and role-dependent (examples span distributed systems reliability, accessibility and design systems, security architecture, data pipelines, performance optimization, mobile platforms) - the interviewer should probe the candidate's own stated specialization rather than assume a fixed domain.
Dashboard Architecture and Layout Design
Focuses on designing effective dashboards that surface the right information quickly and enable exploration. Topics include logical information hierarchy, placing key performance indicators prominently, grouping related metrics, choosing appropriate visualizations for the data and user tasks, and creating visual flow that guides attention. Also covers interactive features such as filtering, drill down, cross filtering, time range controls, and parameterized views; personalization and role based views; accessibility, clarity, and minimizing cognitive load; backend considerations such as data freshness, aggregation and precomputation, query performance, caching strategies, and API design for dashboards; instrumentation, testing and validation with real user scenarios, and trade offs between flexibility and simplicity.
Rapid Problem Definition
Evaluates the ability to quickly synthesize an ambiguous brief into a clear problem statement, scope, constraints, and measurable success criteria. Assesses timeboxed prioritization, clarifying assumptions, identification of edge cases and risks, formulation of testable hypotheses, and succinct stakeholder alignment under pressure.
Company Product and Design Knowledge
Demonstrate a well researched understanding of the company, its major products, target users, market position, and core business model, combined with familiarity with the company design philosophy and visible product design patterns. Prepare to speak about flagship products and features, typical user demographics and needs, the engineering or product challenges the company faces, and how those constraints shape product and design decisions. For design roles, be ready to articulate what you admire about the company design aesthetic, specific patterns or interactions you observe, accessibility and usability trade offs, and how your own design sensibilities or past work align with and could contribute to that aesthetic. For non design roles, emphasize product priorities, technical or operational challenges, and how your skills would help advance those products. Cite concrete examples such as a recent feature, a product workflow, a known engineering challenge, or public design documentation to show you have done focused research.
Artificial Intelligence Assisted Workflows
Covers how professionals use AI tools to accelerate their day to day work: selecting appropriate use cases for AI assistance, iterating on prompts and instructions to get useful output, generating drafts, variations, or code and evaluating them critically, integrating AI generated output into one's own deliverables without introducing errors, validating outputs against requirements, quality standards, or user needs, and recognizing ethical concerns such as bias, over reliance, and misattributed authorship when applying AI in professional work.
Real Time and Offline Experience Design
Design approaches for interactive real time features such as live order tracking and dispatch, and for degraded or offline network conditions. Address latency management, progressive feedback, optimistic updates, eventual consistency, conflict resolution, state reconciliation, caching and retry strategies, and fallback user interfaces. Design clear feedback patterns for transient states and reconnection, reduce user confusion during delays, and define acceptance criteria for degraded modes. Explain how you prototype and validate real time behaviors and coordinate with engineering on push versus poll architectures, data flows, and performance trade offs.