Use FRAME for ambiguous scenarios
Frame the outcome · Reveal constraints · Assess options · Make a bounded plan · Evidence the decision. Do not jump from a vague problem directly to a model or framework.
Role and discovery questions
1. What is a Forward Deployed AI Engineer?
Include customer or business embedding, engineering ownership, discovery through production, adoption, measurable outcome and employer-specific variation.
2. What is your anchor discipline?
Name the capability in which you can independently deliver, then explain the adjacent deployment gaps you deliberately closed.
3. A customer asks for an AI agent to reduce support cost. What do you ask first?
Ask about users, tasks, volume, current workflow, quality and cost baselines, knowledge sources, permissions, unacceptable failures and success criteria. Challenge whether an agent is the right intervention.
4. What would make you stop an AI project?
No material problem, poor or unauthorised data, unacceptable harm, no viable control, cost above value, a better deterministic option, no accountable owner or no credible evaluation.
Architecture and integration
5. Design an enterprise knowledge assistant with role-based access.
Cover source authority, ingestion, metadata, authorization-aware retrieval, model gateway, citations, validation, audit, deletion, feedback and independent retrieval/answer evaluation.
6. How would you integrate AI with ServiceNow or Salesforce?
Define the system of record, API/event pattern, identity, field mapping, idempotency, rate limits, retries, audit, human approval, failure handling and reconciliation.
7. When would you use an agent instead of a deterministic workflow?
Use an agent for bounded interpretation, planning or tool selection when risk can be controlled. Keep fixed policy, permissions and irreversible action deterministic.
8. How do you make a prototype production-ready?
Add representative evaluation, tests, identity, security, resilience, environment separation, CI/CD, observability, cost controls, UAT, approvals, rollback, runbook and adoption measures.
RAG, agents and evaluation
9. Your RAG system produces fluent but unsupported answers. How do you diagnose it?
Separate retrieval from generation. Inspect filters, chunking, metadata, lexical and semantic retrieval, reranking, context assembly, prompt behaviour and citation mapping.
10. How would you build a golden dataset?
Sample real task categories with authorization; include common, edge, rare and adversarial cases; define expected outcomes and rubrics; document provenance; reserve holdout cases and version changes.
11. Can an LLM judge another LLM?
Yes, as one signal. Calibrate against human labels, test bias, use task-specific rubrics, inspect disagreement and preserve human review for high-impact decisions.
12. How do you prevent excessive agency?
Minimum tools and permissions, explicit schemas, validation, allowlists, budgets, step limits, approvals, reversible operations, audit and tested escalation.
13. What is your release threshold?
There is no universal number. Define thresholds by task and risk, including critical-case conditions, evaluator confidence, latency, cost and rollback triggers.
Security, operations and adoption
14. A retrieved document instructs the agent to export records. What happens?
Treat retrieved content as untrusted data. It cannot grant authority. Tool policy, authorization and downstream services must reject the action and preserve safe incident evidence.
15. Model quality drops after a provider update. What do you do?
Confirm the regression, contain risky use, activate rollback or fallback, compare versions on the golden set, communicate impact and release only after evidence recovers.
16. The system is healthy but usage is falling. What next?
Study workflow fit, trust, quality by cohort, training, incentives, friction, overrides and support signals. Treat low adoption as a product and change problem.
17. A customer demands an unsafe two-week launch. What do you say?
Name the missing evidence and consequence, offer a bounded pilot or read-only mode, define the fastest safe gate plan and document residual risk and accountable authority.
18. How do you leave a customer self-sufficient?
Provide architecture, ownership, runbook, evaluations, dashboards, incidents, enablement, change controls and reusable components—then test that the customer can operate them.
Two practice scenarios
Enterprise service-resolution agent
A 4,000-person company wants an agent to retrieve knowledge, recommend a resolution and update the system of record. Knowledge quality and access vary; incorrect updates can trigger compliance incidents.
- Start recommendation-first for a bounded case category.
- Use authorization-aware retrieval and human approval.
- Define quality, safety, cost, rollback and adoption evidence.
Sales opportunity assistant
A CRM team wants summaries, next actions and outreach using CRM, email and usage data. Legal is concerned about personal data; sellers distrust automation.
- Separate recommendation, drafting and send authority.
- Define source, freshness and field-level access.
- Measure adoption and outcome without false causality.
Interview scoring rubric
| Dimension | Weak | Strong |
|---|---|---|
| Problem framing | Accepts the proposed solution | Finds the root issue and compares interventions |
| Architecture | Names tools | Explains boundaries, identity, failure and trade-offs |
| Evaluation | Uses generic accuracy | Builds representative, calibrated release evidence |
| Security | Adds a safety filter | Designs least privilege, audit and containment |
| Operations | Says “monitor it” | Connects SLOs, incident response, fallback, cost and quality |
| Adoption | Assumes users adopt | Measures workflow behaviour and impact against baseline |
Portfolio defence
- Which decision was yours?
- What evidence changed your plan?
- What failed and how was it detected?
- What breaks at ten times the volume?
- Which control is easiest to bypass?
- What impact can you prove rather than infer?
- What would you build differently now?
This independent KDigital guide does not reproduce confidential employer questions or claim to predict any company’s interview process. Use it to practise transferable capabilities.