Senior AI Engineer
Posted Sep 21, 2026 · We last checked this listing on Oct 6, 2026
Likely interview questions for this role
Written from this job description, not a generic list. Each one notes what the interviewer is really checking.
About your past
Tell me about an AI or LLM feature you took from prototype to production. What broke that you did not expect?
What they are checking: Whether they have real production experience and learned from the gaps between demo and reality.
The work is about 75 to 80 percent backend and 20 to 25 percent frontend in React. How comfortable are you building the UI side of an agent feature?
What they are checking: Whether they can actually work end to end, not only on the backend.
What would you do
You work closely with a US team and customers from a different time zone. How do you keep projects moving?
What they are checking: Whether they communicate clearly in writing and plan overlap time so work does not stall.
An agent starts giving wrong answers after a model update. How do you find the cause and fix it?
What they are checking: Whether they have a disciplined debugging approach for non-deterministic systems, including rollback and evals.
About the work
Walk me through how you would design the support automation agent that handles 60 to 70 percent of customer tickets using LangGraph.
What they are checking: Whether they can design a stateful agent graph with tools, routing and handoff to humans that works in production.
How do you decide when an agent should escalate a ticket to a human instead of answering?
What they are checking: Whether they think about confidence, risk and customer impact rather than maximizing automation at all costs.
The voice agent calls carriers to gather and update load information. What can go wrong, and how would you handle it?
What they are checking: Whether they understand latency, misheard data, unclear answers and verification in a real voice workflow.
How do you evaluate an AI agent before and after it goes to production?
What they are checking: Whether they build test sets, metrics and monitoring instead of trusting demos.
Shippers and carriers send data in many formats. How would you design a data integration that stays reliable as partners change their feeds?
What they are checking: Whether they can build robust integrations with validation, retries and clear error handling.
How would you use Redis and PostgreSQL in an agent workflow, and what would you keep in each?
What they are checking: Whether they understand state, caching and persistence trade-offs in backend design for agents.
The carrier onboarding agent uses both email and voice. How would you keep state consistent across those channels?
What they are checking: Whether they can design multi-channel workflows where context is not lost between steps.
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