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PreReqs

AI Engineering

Interviewer personas.

Different interviewers probe different things. These are generic role archetypes to practice adapting your pitch to, not any real person.

  • Principal Architect Interviewer

    Likely focus: Deep technical fluency in reference architecture, RAG design, evaluation, and LLMOps — expects you to go several layers deep on any component you name.

    How to adapt: Lead with a 2-minute reference architecture, then let them pick a component to go deep on rather than pre-emptively over-explaining everything.

  • Data & Governance Interviewer

    Likely focus: Enterprise data foundation maturity — governed ingestion, access control, lineage, quality — and how Gen AI quality depends on it.

    How to adapt: Lead with "data foundation before model excitement" and show that retrieval quality is primarily a data-architecture problem, not a model-selection problem.

  • Delivery & Cost Interviewer

    Likely focus: Delivery governance, roadmap realism, budget ownership, and stakeholder alignment across a program, not just one system.

    How to adapt: Anchor answers in a concrete roadmap/BoM example and speak explicitly to tradeoffs and sequencing, not just the target-state architecture.

  • Confidence-Pass Panel

    Likely focus: Fluency and composure on material you've already covered — this round tests delivery, not new depth.

    How to adapt: Don't introduce new material; tighten and rehearse the answers you already have, and keep every response inside its natural time box.