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

Senior
May 2026

Summary

HarveyAI engineering interview centered on a single deep project walkthrough, where they expect you to own the narrative but also be ready to defend every corner of your design on the spot.

Questions Asked (1)

Q1

Walk us through a project you owned end-to-end: the context, your specific role, the architecture, the key decisions and trade-offs, how you implemented it, what the outcome was, and what you took away from it.

System DesignTechnical Trade-offsAdaptability & Ambiguity
Author's notes

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AI HintsAI Generated

Suggested Approach

Choose a project where you had clear ownership and can articulate the full lifecycle from problem to outcome. Structure your answer as a narrative that highlights your decision-making process, trade-offs, and learnings, tailored to HarveyAI's focus on AI and system design. Be concise but detailed enough to demonstrate technical depth and adaptability.

Pro tip: Quantify the impact of your project (e.g., performance improvements, user adoption) and explicitly connect your learnings to how you would approach similar challenges at HarveyAI. Show that you think like an owner, not just a coder.

1. Set the Context

Briefly describe the project's background, the problem it solved, and why it mattered to the business or users. Keep it high-level to orient the interviewer.

2. Define Your Role

Clearly state your specific responsibilities and ownership. Highlight what you personally drove versus what was team effort.

3. Explain Architecture and Key Decisions

Outline the system architecture, then dive into 2-3 critical technical decisions. For each, explain the trade-offs you considered and why you chose that path.

4. Describe Implementation and Challenges

Summarize how you implemented the solution, focusing on any obstacles you overcame and how you adapted to changes or ambiguity.

5. Share Outcomes and Learnings

Quantify the results (e.g., metrics, user feedback) and reflect on what you learned. Connect the learnings to future work or how you've applied them since.

Key Points to Mention

  • Clear ownership and end-to-end responsibility
  • Architecture overview and rationale for key components
  • Specific trade-offs (e.g., scalability vs. simplicity, build vs. buy) and how you decided
  • Implementation details that showcase technical depth (e.g., handling edge cases, performance tuning)
  • Quantifiable outcomes (e.g., reduced latency by X%, increased user engagement by Y%)
  • Key learnings and how they influence your approach to similar challenges

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