Sr Lead Software Engineer, AI Security Platform
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 time you led technical direction on a platform with several teams contributing. How did you keep it coherent?
What they are checking: Senior leadership through standards, reviews and influence rather than doing all the work personally.
Describe a time you had to push back on a deadline because shipping would have created a security or quality problem.
What they are checking: Judgment and courage to protect quality while still offering a path forward to stakeholders.
What would you do
A scan of a large codebase is timing out in Azure Functions. How do you approach the problem?
What they are checking: Debugging and architecture judgment around serverless limits and when to move work elsewhere.
Developers complain the scanner's findings are hard to act on. What would you change?
What they are checking: Focus on adoption and developer experience, since an unused security tool reduces no risk.
About the work
How would you design a Python orchestration framework that runs many security scans in parallel inside containers?
What they are checking: Practical system design covering job queuing, isolation, retries and resource limits for a scanning platform.
The AI scanner reports a vulnerability that turns out to be a false positive. How would you build validation to cut those down?
What they are checking: Whether they understand that trust in an AI security tool depends on validating findings before developers see them.
How would you use Azure AI Foundry in this platform, and what would you watch for around cost and latency?
What they are checking: Hands-on familiarity with hosted model services and the operational trade-offs of calling them at scale.
How do you protect the scanner itself, given it reads sensitive source code and talks to an AI model?
What they are checking: Security thinking about the platform's own attack surface, including data exposure and prompt injection from scanned code.
How would you structure the React dashboard so security teams and developers each get what they need from the results?
What they are checking: Product sense in front-end design for different audiences, not just component knowledge.
How would you evaluate whether a new model version makes the scanner better or worse before rolling it out?
What they are checking: Whether they think in test sets and measurable evaluation, which is essential for AI-driven tools.
How would you design the Azure SQL data model for findings so you can track a vulnerability across repeat scans?
What they are checking: Data modeling skill for deduplication and history, which makes results useful over time.
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Practice this out loudThe full job description
As published by Northern Trust.