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OtterAI·Software Engineer·Hiring Manager Screen·Intermediate

IntermediateRejected
Jun 2026

Summary

Did a project deep dive for a Software Engineer role at OtterAI and got rejected with zero useful feedback. The whole thing felt fine from my end, which somehow made it worse.

Questions Asked (1)

Q1

Walk me through a project you've worked on in depth.

Technical Trade-offsAdaptability & Ambiguity
Author's notes

I thought it went well.

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AI HintsAI Generated

Suggested Approach

Choose a project where you navigated significant ambiguity or changing requirements, and structure your answer using the STAR method. Focus on your specific contributions, the technical decisions you made, and the measurable impact on the customer or business.

Pro tip: Amazon values Ownership and Customer Obsession—frame your project around a customer problem and highlight times you took initiative beyond your assigned tasks. Quantify results with metrics (e.g., latency reduction, cost savings) to demonstrate tangible impact.

1. Set the Context

Briefly describe the project's purpose, the customer problem it solved, and the team structure. Keep it concise to leave time for your actions and results.

2. Highlight the Ambiguity

Explain what was unclear at the start—such as undefined requirements, technical unknowns, or shifting priorities—and why it was challenging.

3. Detail Your Actions

Walk through the specific steps you took to drive the project forward, including how you made decisions, collaborated with others, and adapted to changes.

4. Share the Results

Quantify the outcomes with metrics (e.g., performance improvements, cost savings, user adoption) and explain the impact on the customer and business.

5. Reflect on Learnings

Summarize what you learned and how you applied those lessons to future projects, showing growth and self-awareness.

Key Points to Mention

  • The specific customer problem and how you prioritized it
  • Technical decisions you made and trade-offs considered
  • How you navigated ambiguity or changing requirements
  • Your individual contributions versus team efforts
  • Quantifiable results (e.g., latency reduction, cost savings, revenue impact)
  • Key learnings and how you applied them later

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