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).
Deep Technical Expertise and Project Mastery
In depth exploration of the candidate's most complex technical work and domain expertise. Interviewers will probe architectural decisions, design trade offs, performance and reliability considerations, algorithmic or model choices, and the reasoning behind technology selections. Candidates should be ready to walk through a single complex backend or artificial intelligence and machine learning system in detail, explain low level technical choices, discuss alternatives considered, describe challenges overcome, and justify outcomes. Expect follow up questions that test depth of understanding and the ability to defend decisions under scrutiny.
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.
Architecture and Technical Trade Offs
Centers on system and solution design decisions and the trade offs inherent in architecture choices. Candidates should be able to identify alternatives, clarify constraints such as scale cost and team capability, and articulate trade offs like consistency versus availability, latency versus throughput, simplicity versus extensibility, monolith versus microservices, synchronous versus asynchronous patterns, database selection, caching strategies, and operational complexity. This topic covers methods for quantifying or qualitatively evaluating impacts, prototyping and measuring performance, planning incremental migrations, documenting decisions, and proposing mitigation and monitoring plans to manage risk and maintainability.
Making Difficult Technical Decisions
Situations where you had to make trade-offs, navigate competing priorities, or choose between technical approaches with real consequences.
Scalable System Design and Architecture
Focuses on designing systems that scale to large numbers of users and high load while balancing consistency, availability, and operational concerns. Candidates should discuss application programming interface design, data flow, load distribution and load balancing, caching strategies, database selection and partitioning, indexing, replication, consistency models, microservices boundaries, synchronous and asynchronous communication patterns, message and event architectures, deployment and rollout strategies, and measures for capacity planning and performance optimization. Answers should include trade off analysis, expected bottlenecks, quantification where possible, and rationale for architecture decisions.
Project Deep Dives and Technical Decisions
Detailed personal walkthroughs of real projects the candidate designed, built, or contributed to, with an emphasis on the technical decisions they made or influenced. Candidates should be prepared to describe the problem statement, business and technical requirements, constraints, stakeholder expectations, success criteria, and their specific role and ownership. The explanation should cover system architecture and component choices, technology and service selection and rationale, data models and data flows, deployment and operational approach, and how scalability, reliability, security, cost, and performance concerns were addressed. Candidates should also explain alternatives considered, trade off analysis, debugging and mitigation steps taken, testing and validation approaches, collaboration with stakeholders and team members, measurable outcomes and impact, and lessons learned or improvements they would make in hindsight. Interviewers use these narratives to assess depth of ownership, end to end technical competence, decision making under constraints, trade off reasoning, and the ability to communicate complex technical narratives clearly and concisely.
Architecture Trade Offs and Cost Analysis
Covers making and communicating architectural decisions that balance trade offs across cost, performance, reliability, speed to market, and organizational complexity. Topics include comparing architectural approaches and tool selections, estimating and explaining costs such as licensing, implementation, maintenance, compute, storage, and data transfer, and understanding how costs scale. Includes business driven framing of technical decisions, cloud economics including capital expenditure versus operational expenditure, return on investment analysis, and Total Cost of Ownership considerations. Candidates should be able to perform rough cost estimation, describe cost optimization strategies including rightsizing and managed service trade offs, and explicitly articulate constraints and choices when prioritizing features, timelines, and resources.
Technical Challenges and Opportunities
This topic covers a candidate's ability to understand, evaluate, and engage with the concrete technical challenges and project opportunities a team is addressing. Candidates should be able to ask about and explain the current system architecture, infrastructure initiatives, and stack choices; identify major architecture trade offs and areas of technical debt; and describe scalability, performance, and reliability concerns. They should be able to evaluate projects such as migrations, infrastructure scaling, developer tooling improvements, reliability and observability work, and platform changes in terms of design decisions, trade offs, testing strategies, rollout and deployment approaches, rollback and maintenance plans, and long term operability. Candidates should demonstrate familiarity with operational practices including monitoring and observability, incident response and postmortems, service level objectives and error budgets, continuous integration and continuous delivery, and capacity planning. The topic assesses problem framing, prioritization, and impact thinking by asking how engineering work moves key product metrics and user experience, and it invites discussion of how engineers at different seniority levels can contribute through execution, ownership, mentorship, and technical leadership.
Technical Depth and System Understanding
Demonstrated ability to quickly grasp complex technical domains and explain system design, architecture, and tradeoffs. Cover distributed systems fundamentals, application programming interfaces, software architecture patterns, performance and scalability concerns, reliability considerations, and approaches to validating technical accuracy. In interviews, present concrete examples from projects that highlight how you diagnosed technical problems, evaluated alternatives, and made design decisions while communicating clearly to non technical stakeholders.