AI Intelligent Automation, Director
Posted Sep 17, 2026 · We last checked this listing on Oct 5, 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 automation that failed in production. What happened and what did you change in your engineering practices afterward?
What they are checking: Whether they learn from failures and turn them into standards for testing, monitoring and change control.
Tell me about building or growing a team of automation engineers. How did you raise their engineering standards?
What they are checking: Whether they can lead people and lift a team from scripting habits to production-grade engineering.
What would you do
You inherit dozens of one-off automations built by different teams with no shared standards. What do you do in your first ninety days?
What they are checking: Whether they can rationalize a messy estate and reduce dependence on isolated solutions without stalling the business.
How would you work with security and infrastructure teams when an automation needs elevated access to several systems?
What they are checking: Whether they treat credentials and access as a design concern and partner with security rather than working around it.
A business leader wants an automation in two weeks, but doing it properly will take six. How do you handle that conversation?
What they are checking: Whether they can protect quality while still finding a way to deliver value quickly.
About the work
How do you decide whether a business problem should be solved with Power Platform, UiPath, a direct API integration, custom code, or an AI capability?
What they are checking: Whether they choose the right automation approach on merit instead of forcing every problem into one tool.
Walk me through a reference architecture you'd put in place for enterprise automation that has to be secure, reusable and supportable in production.
What they are checking: Whether they can design for scale and operations, not just build bots that work in a demo.
How do you bring LLMs or other AI capabilities into automation workflows while keeping them reliable and auditable in a healthcare-adjacent company?
What they are checking: Whether they understand the risks of nondeterministic AI and have practical guardrails for it.
How do you measure the value of an automation program and report it to executives?
What they are checking: Whether they can show real business outcomes rather than counting bots or hours claimed on paper.
How do you set up quality engineering and testing for RPA and Power Platform solutions that depend on UIs and systems that change?
What they are checking: Whether they know how fragile UI-based automation is and how to test and monitor it before it breaks.
How would you build a reusable component library so teams stop rebuilding the same connectors and logic?
What they are checking: Whether they can create shared assets that people actually adopt instead of an unused catalog.
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Practice this out loudThe full job description
As published by Vizient.