Sr Associate Software Engineer, AI Security
Posted Sep 22, 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 a cloud-native application you built and secured. What decisions did you make about identity and secrets?
What they are checking: Whether they have real experience securing cloud applications end to end.
Tell me about a time you built a user-facing application. How did you decide what the user needed to see?
What they are checking: Whether they can design interfaces, which the role requires alongside back-end work.
What would you do
A development team says the scanner flagged something that isn't a real issue and they're frustrated. How do you respond?
What they are checking: Whether they treat user feedback as a signal to improve the tool rather than dismissing it.
A new model version comes out. How would you decide whether to switch the scanner to it?
What they are checking: Whether they would evaluate with a test set and compare results rather than upgrade on hype.
About the work
Our platform uses frontier AI models to find, validate and report vulnerabilities in enterprise codebases. How would you cut down false positives so developers trust the results?
What they are checking: Whether they understand that a noisy scanner gets ignored, and know how to add validation steps around model output.
How would you design the pipeline that sends code to an AI model for analysis while keeping sensitive source code secure?
What they are checking: Whether they think about data handling, access control and where code goes when using external AI services.
What are some common vulnerability classes you'd expect the scanner to catch, and how would you confirm one is real?
What they are checking: Whether they know OWASP-style flaws well enough to validate findings rather than trust them blindly.
How would you defend the scanner itself against prompt injection hidden in the code it reads?
What they are checking: Whether they see that untrusted input can manipulate an AI system and know how to limit the damage.
How would you scale the scanner to run across thousands of repositories without huge cost or delay?
What they are checking: Whether they think about batching, caching, incremental scans and model costs.
How do you measure whether the scanner is actually making the firm's code more secure?
What they are checking: Whether they connect the tool to outcomes like fixed vulnerabilities, not just number of findings.
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Practice this out loudThe full job description
As published by Northern Trust.