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).
Technical Differentiation and Architecture
Evaluating and articulating how technical design and product architecture create competitive advantage. Covers understanding architecture choices, data flows, integration points, scalability and security trade offs, and how those technical differences influence buyer decisions. Includes ability to explain why particular technical decisions matter to enterprise architects and developers and to identify architectural improvements that enhance differentiation.
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.
Distributed Systems Fundamentals
Core principles and theory that underlie distributed computing systems. Includes understanding trade offs between consistency, availability, and partition tolerance, common consistency models such as eventual and strong consistency, replication and sharding strategies, load balancing and data partitioning, consensus algorithms and their guarantees, scalability and fault tolerance patterns, and how these concepts apply to infrastructure components such as databases, caches, service meshes, and load balancers. Candidates are expected to explain design choices, common failure modes, and how fundamental concepts influence architecture decisions for resilient and scalable systems.
Solution Architecture and Proof of Concepts
Describe how you design and deliver solution architectures and proof of concept demonstrations that showcase product capabilities and technical value. Cover scoping requirements with customers or sales, building reproducible demos, integration patterns, documentation and runbooks, success criteria, iteration cycles and how you collaborate with engineering and product to operationalize demonstrations for sales and marketing.
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.