Information Security AI Strategy Intern

We are seeking a high-caliber, inquisitive intern to perform a comprehensive audit of our existing Information Security technology stack through the lens of Artificial Intelligence. Your mission is to identify manual, high-friction, or data-heavy security processes and design AI-driven frameworks to automate or enhance them.

This is not just a "shadowing" role; you will be responsible for building a roadmap of five high-impact AI implementation projects that will influence our security strategy for the coming year.
 

Key Responsibilities

• Tech Stack Audit: Perform a deep dive into our current security tooling (SIEM, EDR, Firewall, IAM, and GRC platforms) to understand data flows and manual touchpoints.

• Gap Analysis: Identify "toil"—repetitive tasks performed by security engineers—that are ripe for optimization via Machine Learning (ML) or Large Language Models (LLMs).

• Use Case Development: Research and design five specific project proposals. This includes defining the problem statement, the AI/ML approach (e.g., NLP for policy review, anomaly detection for logs), and the expected ROI.

• Feasibility Assessment: Evaluate the data privacy and security risks associated with deploying AI within the security stack (e.g., prompt injection, data leakage).

• Stakeholder Briefing: Present your final "AI in Security" roadmap to the CISO and senior leadership.

The Deliverable

The cornerstone of this internship is a Strategic AI Opportunities Report, detailing five distinct projects. Each project summary must include:

1. Current State vs. Future State: A "before and after" workflow analysis.

2. Technical Approach: The specific AI model type or toolset required.

3. Outcome Metrics: Expected reduction in Mean Time to Detect (MTTD), Mean Time to Respond (MTTR), or manual hours saved.

4. Risk Profile: Potential pitfalls or biases the AI might introduce.

Examples of Potential Projects

• Automated Firewall Audit: Using LLMs to parse complex firewall port requests against existing security policies to flag "high-risk" openings automatically.

• Identity Analytics: Applying clustering algorithms to identify stale, risky or unprotected AWS access keys.

• Incident Summary Generation: Automating the creation of post-mortem reports by synthesizing SIEM alerts and analyst notes into a cohesive narrative.