Technical practice
How would you design an AI agent workflow for a customer-service request?
What to coverThe posting calls for scalable agents and agentic workflows using LangChain, LangGraph, or similar frameworks. Suggested preparation: explain how you would define workflow steps, coordinate tool calls, manage state, and decide when the agent should stop or seek assistance.
How would you keep customer-service automation responsive during peak demand or irregular operations?
What to coverThe role explicitly addresses high-volume customer requests, including irregular operations. Suggested preparation: discuss capacity, latency, graceful degradation, and the trade-off between faster responses and reliable resolution.
How would you integrate a conversational agent across voice and chat channels?
What to coverThe posting calls for voice automation and conversational AI integrated with customer-service channels. Suggested preparation: describe what conversation state and service APIs could be shared, what differs by channel, and how you would test the customer experience.
How would you design and evaluate a retrieval-augmented response?
What to coverRAG patterns, prompt engineering, and vector databases appear in the posting. Suggested preparation: explain retrieval and prompt design, then compare responses for relevance, grounding, latency, and cases where retrieved information is insufficient.
How would you structure maintainable agent code and its service integrations?
What to coverThe role calls for documented Python, TypeScript, and .NET/C# code, plus API integration, object-oriented design, and SQL and NoSQL knowledge. Suggested preparation: explain module boundaries, API contracts, data-store choices, and how you would test integrations without tightly coupling the agent to a channel.
How would you choose an AWS deployment approach for an agent workflow?
What to coverAWS implementation is required, while Lambda, Step Functions, API Gateway, S3, DynamoDB, ECS, EC2, and event-driven processing are listed as preferred experience. Suggested preparation: compare appropriate managed and compute options against workflow duration, asynchronous work, scaling, and operational complexity rather than assuming one prescribed stack.
How would you diagnose an agent that starts giving poor answers or failing requests?
What to coverThe posting includes testing, debugging, production support, and analyzing code to find errors. Suggested preparation: walk through separating retrieval, prompt, orchestration, API, and application-code failures, including what you would log or measure while protecting customer information.
What safeguards would you build into a customer-facing AI agent?
What to coverSecurity protocols, code quality, responsible AI, and AI governance are named in the posting. Suggested preparation: discuss access controls, sensitive-data handling, unsafe or unsupported responses, and how you would verify safeguards without claiming a particular United policy.
How would you determine whether a new agent or prompt improves customer-service outcomes?
What to coverThe role emphasizes faster resolution and reduced wait times; A/B testing and experimentation are preferred experience. Suggested preparation: propose outcome and quality measures, compare alternatives, and explain how you would detect improvements that come at the expense of accuracy or customer experience.
How would you take an agent change from prototype to maintainable release?
What to coverThe posting covers prototyping, the full Agile lifecycle, documentation, and deployment; CI/CD and infrastructure as code are preferred. Suggested preparation: outline testing, review, deployment, monitoring, and rollback considerations, distinguishing posting requirements from your proposed approach.
Behavioural practice
Tell me about a time you translated an ambiguous user need into a technical specification.
What to coverThe role involves analyzing user needs and writing specifications from business requirements. Suggested preparation: use a real situation/action/result example showing how you clarified the need, made design decisions, and checked that the result met it.
Describe a time you refined a solution after feedback from end users.
What to coverThe posting calls for collaborating with end users to prototype, refine, test, and debug agents. Suggested preparation: give a real situation/action/result example that distinguishes the feedback, your changes, and the observed outcome.
Tell me about a time you made a technical trade-off while working independently.
What to coverThis senior role calls for independently building solutions and contributing to architectural decisions. Suggested preparation: use a real situation/action/result example explaining the alternatives, your reasoning, how you communicated the decision, and its result.
Describe a difficult defect you investigated and supported through resolution.
What to coverTroubleshooting code and supporting automation workflows are stated responsibilities. Suggested preparation: give a real situation/action/result example covering diagnosis, the fix or mitigation, and what you did to prevent recurrence.
Tell me about coordinating delivery across teams with different priorities.
What to coverThe posting names AI/ML engineers, data scientists, product teams, employees, and vendor contractors as collaborators. Suggested preparation: use a real situation/action/result example showing how you aligned requirements and responsibilities, resolved a disagreement, and delivered an outcome.