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).
Systems Design and Scalability
Focuses on designing scalable distributed systems and marketplace architectures. Topics include core marketplace components such as search and discovery, real time availability, booking and reservation flows, payment processing, and host to guest matching and how those systems interact. Expect to identify scalability bottlenecks, propose caching strategies, database optimization including sharding and replication, horizontal scaling approaches, and reason about consistency versus availability trade offs. Also cover real time synchronization strategies, handling race conditions such as double booking, event driven designs and message based architectures, and considerations for monitoring and operational resilience.
Marketplace Core Systems
Core marketplace systems architecture covering the Booking, Search, and Listings subsystems. Includes service decomposition into microservices, API design and inter-service communication, data consistency models (strong vs eventual), search indexing and relevance, catalog/listing management, booking workflows and orchestration, cross-service transactions, caching strategies, scalability, fault tolerance, and multi-region/global distribution considerations in a marketplace platform.
Autonomous Vehicles and Platform Integration
Assess the candidate's understanding of autonomous vehicle technology and how to integrate such fleets into a rideshare or mobility platform. Topics include the core technical stacks for perception localization mapping planning and control; hardware and sensor constraints and associated data pipelines; edge computing and connectivity considerations; release engineering including over the air updates; simulation based testing and hardware in the loop validation; safety engineering and verification processes; and real time telemetry and incident analysis. Interviewers should also probe operational integration such as fleet management dispatching and matching algorithms pricing and rider experience changes; maintenance and teleoperation strategies; model training and data collection workflows; partnerships with vehicle manufacturers and suppliers; insurance and regulatory considerations across markets; incremental rollout strategies and risk mitigation. Evaluate trade offs among latency cost safety and reliability when choosing architectures and the candidate's approach to timelines governance and cross functional coordination.
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.
System Design and Architecture
Design large scale reliable systems that meet requirements for scale latency cost and durability. Cover distributed patterns such as publisher subscriber models caching sharding load balancing replication strategies and fault tolerance, trade off analysis among consistency availability and partition tolerance, and selection of storage technologies including relational and nonrelational databases with reasoning about replication and consistency guarantees.
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.
Data Consistency and Distributed Transactions
In depth focus on data consistency models and practical approaches to maintaining correctness across distributed components. Covers strong consistency models including linearizability and serializability, causal consistency, eventual consistency, and the implications of each for replication, latency, and user experience. Discusses CAP theorem implications for consistency choices, idempotency, exactly once and at least once semantics, concurrency control and isolation levels, handling race conditions and conflict resolution, and concrete patterns for coordinating updates across services such as two phase commit, three phase commit, and the saga pattern with compensating transactions. Also includes operational challenges like retries, timeouts, ordering, clocks and monotonic timestamps, trade offs between throughput and consistency, and when eventual consistency is acceptable versus when strong consistency is required for correctness (for example financial systems versus social feeds).
System Architecture and Reliability
Covers end to end architecture thinking, the rationale behind design choices, and operational practices to maintain system health. Topics include how to decompose services and data flows, define and justify architectural trade offs, plan for high availability and disaster recovery, implement monitoring and logging, define service level objectives and indicators, handle incident response and postmortem learning, and incorporate security and threat mitigation into architecture and operations. Candidates should be able to explain the business impact of architecture decisions and trade offs between cost, complexity, and reliability.
System Evolution and Technical Strategy
Approaches for evolving systems and planning long term technical direction. Topics include managing technical debt, planning incremental migrations or rewrites, roadmapping, versioning and backward compatibility, deprecation strategies, balancing short term product needs with long term architecture, and aligning technical strategy with business objectives. Good answers show a pragmatic plan for incremental change, governance, and measurable milestones.