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OpenAI

Senior

Embed with security teams to deploy OpenAI models safely into real cybersecurity workflows

OpenAI is hiring a customer-facing Cyber AI Deployment Engineer to help CISOs, SOC teams, and security engineers apply OpenAI models, APIs, Codex, and agentic workflows to use cases like secure code review, vulnerability triage, threat modeling, and incident response. The role demands 5+ years of technical consulting or security-architecture experience plus hands-on build skills (APIs, agents, CI/CD, security tooling) and evidence-first security judgment. Expect the interview to test cybersecurity domain depth, ability to design safe AI deployment patterns, and fluency moving between CISO-level strategy and hands-on implementation.

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这场面试考什么

  • Cybersecurity domain depth (AppSec, cloud security, SOC/IR, detection engineering, GRC)
  • Safe AI deployment patterns: tool/function calling, sandboxing, guardrails, telemetry, human-in-the-loop
  • Scoping pilots from ambiguous customer pain (success criteria, data, evaluation, decision gates)
  • Translating between CISO-level strategy and practitioner-level implementation
  • Evidence-first security judgment: validating findings, avoiding overstated claims
  • Building demos/prototypes/reference architectures with real security tooling (APIs, CLIs, CI/CD, scanners)

常见提问方向

How would you scope a pilot for an AI-assisted vulnerability triage or SOC workflow with a security team?

What safe implementation patterns (guardrails, sandboxing, human approval) would you build into an agentic security workflow?

How do you translate a CISO's strategic goals into a concrete technical deployment plan for a security engineering team?

Describe a time you had to validate a security finding and separate a true positive from noise

Walk me through a demo or proof-of-concept you built integrating AI with real security tooling (CI/CD, scanners, logs)

How would you advise a customer on data handling and auditability requirements for an AI-powered incident-response workflow?

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