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Series B+ Startup·Software Engineer·Onsite - System Design / Architecture·Senior

Senior
May 2026

Summary

System design round for a software engineer role, one question about building a support ticket agent system with some awkward constraints baked in. Not a lot of context given upfront, had to ask clarifying questions to figure out what they actually wanted.

Questions Asked (1)

Q1

Design an agent-based ticket support system where agents use a browser to read tickets from a system with no API, while a separate user system with an API is used to fetch user data and generate chat responses.

System DesignAPI & IntegrationsTechnical Trade-offs
Author's notes

The no-API constraint on the ticket system is what threw me.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then propose a high-level architecture that separates the browser automation layer from the API integration and response generation. Discuss trade-offs between reliability, speed, and cost, and outline how components communicate and handle failures.

Pro tip: Emphasize idempotency and observability: design the browser automation to be resilient to UI changes and ensure every action is logged and traceable. This shows you think about production readiness, not just functionality.

1. Clarify Requirements and Constraints

Ask questions to understand ticket volume, latency requirements, user data sensitivity, and whether browser automation is temporary. This ensures the design meets actual needs.

2. High-Level Architecture

Sketch components: a browser automation service (e.g., using Puppeteer/Playwright) to fetch tickets, an API client for user data, a response generator (possibly LLM-based), and an orchestrator. Define data flow and interfaces.

3. Detailed Component Design

For each component, discuss implementation choices: headless browser management, session handling, API rate limiting, caching, and prompt engineering for chat responses. Address error handling and retries.

4. Trade-offs and Scalability

Analyze trade-offs: browser automation vs. reverse-engineering APIs, synchronous vs. asynchronous processing, and cost of LLM calls. Discuss scaling horizontally and handling UI changes.

5. Reliability and Monitoring

Propose logging, metrics, and alerting for browser failures and API errors. Suggest fallback mechanisms and manual override options.

Key Points to Mention

  • Browser automation tools like Puppeteer or Playwright, and strategies to handle dynamic content and anti-bot measures.
  • API integration best practices: authentication, rate limiting, error handling, and caching user data.
  • Response generation: using LLMs with context from tickets and user data, and managing token limits and latency.
  • Asynchronous processing and queueing (e.g., using a message broker) to decouple ticket fetching from response generation.
  • Idempotency and exactly-once processing to avoid duplicate responses.
  • Observability: structured logging, metrics (e.g., ticket processing time, success rate), and alerting.

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