Agentic AI Interview
Experienced Hire

How senior engineers get evaluated
Target Roles
• Backend Engineers
• ML Engineers
• Platform Engineers
• AI Engineers (3+ years)
Interview Focus
• System design thinking
• Production experience
• Failure handling and trade-offs

Q1: Multi-Agent vs Single Agent

“When would you choose a single agent instead of a multi-agent system?”
What the Interviewer Is Testing
• Context‑driven architecture decisions
• Trade-off thinking
• Production cost and latency awareness
Strong Answer Signals
• Clarifies constraints before answering
• Mentions latency and orchestration cost
• Explains failure domain isolation
• Gives scenario‑based justification
Weak Answer Signals
• “Multi‑agent is always better”
• “Single agent is simpler so start there”
• No cost or latency discussion
Follow-up: How would you observe failures here?
What changes at 10× traffic? How do you debug this in prod?

Q2: Planner vs Executor Roles

“Why separate planner and executor agents?”
What the Interviewer Is Testing
• Failure isolation understanding
• Control and observability mindset
Strong Answer Signals
• Planner owns state and decisions
• Executors are constrained and replaceable
• Mentions retry and substitution logic
Weak Answer Signals
• “Just a design pattern”
• Only “cleaner code” explanation
Follow-up: What happens if the planner crashes?
How do you replay execution?

Go From “LLM User” to “Production Engineer”

🚀 Agentic AI Enterprise Bootcamp
Practice answering real interview scenarios
and designing production-grade agentic systems.
Inside the Bootcamp:
• System design for agentic AI
• Failure handling and observability patterns
• Evaluation and human-in-the-loop design
• Architecture trade-offs from real projects
Next Cohort: February 15, 2025
Enroll Now
For senior engineers with 3+ years experience
Ship safe, observable agents.
That’s what interviewers are really looking for.