Senior
Threat-model Reddit's AI/agentic products and turn findings into reusable security guardrails
This role sits in Reddit's Privacy and Assurance org securing AI-powered products: LLM integrations, agentic workflows, MCP servers, and internal AI tools. It is explicitly not an MLE role — the bar is application security judgment plus the builder instinct to turn one-off findings into scanners, guardrails, and platform controls.
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What this interview tests
- Threat modeling LLM/agentic systems and MCP servers
- AI-specific attack classes: prompt injection, jailbreaks, tool poisoning, data leakage
- Building reusable security primitives (guardrails, scanners, policy checks, sandboxes)
- Trust boundary analysis across inference/retrieval/tool-use/execution paths
- Launch risk judgment and remediation sequencing
- Communicating technical risk to engineers, PMs, and leadership
Common question themes
Threat model a hypothetical AI feature that uses MCP tools and retrieval
How would you detect and prevent prompt injection in an agentic workflow
Turning a one-off AI security finding into a scalable guardrail or scanner
Deciding whether to block a product launch over a security risk
Reasoning about trust boundaries: user input vs model context vs tool calls
Explaining AI security risk to a non-technical stakeholder
Prior application security fundamentals: code review, vulnerability triage
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