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Capital One

Tech-first US bank hiring AI engineers for LLM platforms, fraud and credit

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Interview in a few hours? A quick sprint for Capital One

AI in interviews

low confidence

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

Checked 23 Oct 2026Source

Typical interview loop

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

  1. Recruiter screen

    Focus: Background, team match

    A first call with an AI/ML recruiter about your background and the team; recruiters suggest asking which team you'll meet, since it shapes the technical questions.

  2. CodeSignal coding assessment

    Focus: DSA fundamentals, Python

    A 70-minute, four-question data-structures-and-algorithms test taken in one sitting within about 10 days of the invite, graded pass/fail.

  3. Hiring manager interview

    Focus: Experience, team fit

    After a resume review, a 30-minute conversation with the hiring manager about your experience and fit for the team.

  4. Power Day: coding and AI/ML depth

    Focus: Live coding, ML depth

    An hour split between live coding in CodeSignal and a deep discussion of your AI/ML skills as they relate to the team's work, with interviewers giving hints and watching how you use them.

  5. Power Day: AI system design

    Focus: LLM system design

    You design an end-to-end system built on modern LLM concepts, covering components, trade-offs and how it would run in production.

  6. Power Day: case and behavioral

    Focus: Business reasoning, ownership

    A case interview on a public Capital One product where you reason to a clear recommendation, plus a STAR-style behavioral round; all four Power Day rounds carry equal weight.

How it weights your plan

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

System design+30%
ML fundamentals+20%
Behavioral+20%
Coding+10%

Official prep and resources

Public candidate write-ups

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