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Salesforce·Software Engineer·Onsite - System Design / Architecture·Senior

Senior
May 2026

Summary

Salesforce system design onsite with two distinct halves: you present your own system, then they flip it and hand you something from their world. The whole thing is deliberately loose, which sounds fun until you're actually in it.

Questions Asked (2)

Q1

Walk us through the architecture of a system you've built or worked on closely, covering components, data flow, how it scales, and the trade-offs you made.

System DesignTechnical Trade-offsAdaptability & Ambiguity
Author's notes

This sounds like a gift because you're talking about your own stuff, but I kind of rambled for the first few minutes before finding a thread.

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AI HintsAI Generated

Suggested Approach

Choose a system you know deeply and can discuss end-to-end, then structure your answer around requirements, high-level architecture, component deep-dives, scaling, and trade-offs. Use a whiteboard or verbal diagram to make the flow clear, and tie every decision back to a specific constraint or goal.

Pro tip: Explicitly state the non-functional requirements (scale, latency, consistency) upfront, because at Salesforce the interviewer cares as much about why you chose a design as the design itself. Also, be honest about what you'd change today—it shows growth and self-awareness.

1. Set the Context and Requirements

Briefly describe the system's purpose, users, and key functional and non-functional requirements (e.g., scale, latency, consistency). This anchors the rest of your answer and shows you can scope a problem.

2. Sketch the High-Level Architecture

Walk through the major components (e.g., clients, API gateway, services, databases, queues, caches) and how they connect. Use a simple diagram or verbal map to make the structure easy to follow.

3. Trace the Data Flow

Follow a typical request or data item through the system, explaining how it moves between components, where it's transformed, stored, and retrieved. Highlight any asynchronous or event-driven flows.

4. Explain Scaling and Reliability

Describe how the system handles growth (e.g., horizontal scaling, sharding, caching, load balancing) and ensures reliability (e.g., redundancy, failover, monitoring). Mention specific bottlenecks and how you addressed them.

5. Discuss Trade-offs and Lessons Learned

Articulate the key trade-offs you made (e.g., consistency vs. availability, latency vs. cost, build vs. buy) and why. Share what you'd do differently now and what you learned.

Key Points to Mention

  • Clear separation of concerns and modularity in component design
  • Use of caching, load balancing, and horizontal scaling to handle traffic growth
  • Data storage choices (SQL vs. NoSQL, sharding, replication) and their implications
  • Asynchronous processing and message queues for decoupling and resilience
  • Monitoring, logging, and alerting for operational visibility
  • Specific trade-offs (e.g., CAP theorem, latency vs. consistency) and how they were resolved

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q2

Here's an architecture from our domain. What problems do you see with it, and how would you improve it?

System DesignTechnical Trade-offsAdaptability & Ambiguity
Author's notes

Genuinely did not see this part coming.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the architecture's goals, constraints, and scale before critiquing. Then systematically evaluate it across key dimensions like scalability, reliability, and maintainability, and propose improvements with clear trade-offs. Frame your answer as a collaborative problem-solving discussion, not a fault-finding mission.

Pro tip: Always tie your critiques to business impact and user experience, and acknowledge what the architecture does well before suggesting changes. This shows you can balance technical rigor with pragmatism and empathy for existing design decisions.

1. Clarify Requirements and Context

Ask questions to understand the system's purpose, expected scale, SLAs, and constraints. This ensures your analysis is relevant and grounded in real needs.

2. Identify Strengths and Weaknesses

Acknowledge what works well, then systematically evaluate the architecture against key quality attributes like scalability, availability, consistency, and cost.

3. Prioritize Problems by Impact

Focus on the most critical issues that could cause outages, data loss, or major performance bottlenecks. Avoid getting lost in minor details.

4. Propose Improvements with Trade-offs

Suggest concrete changes, explaining how they address the problems and what trade-offs they introduce (e.g., complexity, cost, latency).

5. Summarize and Validate

Recap your key points and invite feedback to ensure alignment and show openness to alternative perspectives.

Key Points to Mention

  • Scalability bottlenecks (e.g., single points of failure, database sharding, caching strategies)
  • Reliability and fault tolerance (e.g., redundancy, failover, circuit breakers)
  • Data consistency and integrity (e.g., CAP theorem trade-offs, eventual consistency)
  • Maintainability and operability (e.g., monitoring, logging, deployment complexity)
  • Cost and resource efficiency (e.g., over-provisioning, cloud spend)
  • Security and compliance (e.g., data encryption, access controls, multi-tenancy)

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.