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Ramp

Spend management with AI that reads receipts and flags policy breaks

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Interview in a few hours? A quick sprint for Ramp

AI in interviews

low confidence

No public policy found. Assume no AI assistance in live rounds unless your recruiter says otherwise.

Checked 25 Oct 2026Source

Typical interview loop

How Ramp usually runs it for applied AI and LLM engineer roles.

  1. Recruiter screen

    Focus: Motivation and AI fluency

    A 25 to 30 minute call on background and motivation; some candidates say it centred on how they use AI day to day.

  2. CodeSignal assessment

    Focus: Incremental implementation speed

    A 90-minute online test built as one problem that grows across four levels of added requirements.

  3. Technical phone screen

    Focus: Working code and edge cases

    An hour of live coding in a shared editor; one AI engineer instead got a notebook-based data-analysis session.

  4. Onsite practical and product coding

    Focus: Practical coding and scoping

    Two coding rounds: extending a realistic codebase with messy inputs, and turning a vague product ask into a working feature.

  5. AI-assisted coding (reported)

    Focus: Judgment with AI tools

    A newer round where you build with a tool like Cursor or Claude Code and are scored on prompting, iterating, catching its mistakes and explaining the result.

  6. System design and values

    Focus: Correctness at scale, ownership

    A design round on money-moving systems that stay correct under load, plus a values conversation with the hiring manager.

Topics to prepare for Ramp

The topics its loop weighs most, each with what interviewers check and what to study.

How it weights your plan

Selecting Ramp when you build a plan multiplies each topic’s priority score:

AI coding round+40%
Coding+30%
System design+10%

Official prep and resources

Public candidate write-ups

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