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Workday

HR and finance cloud; building Illuminate AI agents into enterprise workflows

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Interview in a few hours? A quick sprint for Workday

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 Workday usually runs it for applied AI and LLM engineer roles.

  1. Hiring manager or recruiter screen

    Focus: Background, fit

    An opening conversation about your background, past work and team fit that stays high-level and mostly behavioral.

  2. AI projects deep dive

    Focus: Applied AI experience

    Interviewers dig into AI systems you have built and the practical problems you hit, such as context limits and judgment calls under ambiguity.

  3. HackerRank coding assessment or CodePair

    Focus: Coding, communication

    Either a take-home HackerRank test (most allow your own IDE) or a live CodePair session where you talk through your reasoning and take hints.

  4. Technical design and AI architecture panel

    Focus: RAG, agents, design trade-offs

    A discussion with senior engineers on implementation trade-offs, RAG pipeline design and agentic systems, framed as a conversation, not a coding test.

  5. Structured behavioral interviews

    Focus: Core skills, values

    Behavioral interviews built around the job-critical and core Workday skills named in your invite, asking for specific recent examples.

How it weights your plan

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

RAG+40%
Agents+20%
System design+20%
Behavioral+20%
Evals+10%

Official prep and resources

Public candidate write-ups

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