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AI security careers

Every company is adopting AI. Someone has to secure it.

Chatbots, copilots and AI agents are being rolled out faster than security teams can test, govern or protect them. That gap is creating a new kind of security career, and very few applicants are ready for it yet. This is how you get ahead of everyone else.

See the AI Security Track Search AI security jobs
3 career paths5 guided portfolio projectsAI resume templates
~/ai-threat-model
$ review askkestrel-chatbot
# 5 threats found
! high retrieval ignores doc permissions
! high indirect prompt injection via shared files
! med bot can open tickets without approval
✓ fix permission-aware retrieval
✓ fix human confirmation for actions
$
Build this project for your portfolio →
Why now

Business leaders already see AI as the biggest change in security.

From the World Economic Forum's Global Cybersecurity Outlook 2026 survey of business and security leaders:

94%

say AI will be the most significant driver of cybersecurity change in 2026

87%

believe AI-related vulnerabilities have increased, more than any other threat type

64%

now assess AI tools' security before deploying them, up from 37% a year earlier

Source: World Economic Forum, Global Cybersecurity Outlook 2026, as reported by The Register.

What that means for you: every AI tool a company assesses needs someone to test it, review its risks, check its data handling and write the policy around it. Those are the skills in this guide, and most applicants don't have them yet.
Three AI security paths

Pick the one that fits how you like to work

Test & defend

AI Security Analyst / Engineer

Threat-model AI features, test for prompt injection and data leakage, and design monitoring and guardrails.

  • Learn: OWASP Top 10 for LLMs, MITRE ATLAS, AppSec basics, logging
  • Cert path: Security+ → CompTIA SecAI+
  • Comes from: SOC, AppSec, cloud, software dev
Assess & govern

AI Governance & Risk Analyst

Inventory AI use across the company, rate the risks, review AI vendors, and write and enforce AI policy.

  • Learn: NIST AI RMF, ISO/IEC 42001, EU AI Act basics, risk registers
  • Cert path: Security+ or ISC2 CC → IAPP AIGP
  • Comes from: GRC, audit, compliance, legal, project management
Protect data

AI Privacy & Compliance Analyst

Track what data AI tools collect and keep, how vendors process it, and who can access it. Run privacy impact assessments.

  • Learn: data mapping, privacy impact assessments, vendor terms
  • Cert path: Security+ or ISC2 CC → IAPP AIGP or a privacy certification
  • Comes from: privacy, healthcare, legal, data governance

Not sure which one? The 60-second quiz includes both AI paths.

The honest part

AI security is usually a second step, so start building it now.

Most AI security postings expect a security foundation first. The good news: you can build the foundation and the AI layer at the same time. Then you're the candidate with both, and almost nobody has both yet.

1. Get a core security foundation

Security+ level knowledge, plus a first role in SOC, AppSec, cloud or GRC.

2. Learn the AI frameworks (free)

OWASP Top 10 for LLM Applications, MITRE ATLAS, NIST AI RMF.

3. Build AI-specific proof

One AI threat model or risk register in your portfolio sets you apart immediately.

What you'll build

Five AI projects that make a hiring manager stop scrolling

Each one produces a real portfolio piece you can link on your resume and walk through in an interview. The full step-by-step guides are in the Toolkit's AI Security Track.

PROJECT 1

Threat-model an AI assistant

Find the risks in a company chatbot that searches internal documents, using STRIDE, the OWASP Top 10 for LLMs and MITRE ATLAS.

You'll have: a threat model, a data-flow diagram and a launch-readiness summary.

PROJECT 2

Prompt injection test plan

Write and run a professional test plan in authorized practice labs, then report findings the way a security tester would.

You'll have: test cases, results and written findings.

PROJECT 3

AI incident response playbook

Decide what to log, write five detections and plan the response for when an AI feature leaks data or misbehaves.

You'll have: a playbook, a logging spec and a tabletop exercise.

PROJECT 4

AI risk register (NIST AI RMF)

Inventory six AI use cases, rate their risks, and map controls to Govern, Map, Measure and Manage.

You'll have: a risk register and a one-page memo to the CISO.

PROJECT 5

AI vendor privacy assessment

Review a real AI product's public terms for a business use case: training use, retention, subprocessors, DPA.

You'll have: a cited assessment and an approval recommendation.

Every project includes
  • Step-by-step instructions
  • A worked example of finished work
  • Evidence checklist
  • A ready resume bullet
  • Interview talking points
Free 30-minute starter: read the OWASP Top 10 for LLM Applications, then try to beat the first few levels of a prompt-injection practice game like Gandalf. Write down why each defense failed. That's the mindset behind every project above.
Inside the Career Toolkit

The AI Security Track

Everything you need to go after AI security roles, included with the Career Toolkit alongside the core cybersecurity pathways.

  • 5 guided AI security projects: threat modeling, prompt-injection testing, AI incident response, AI risk register, AI vendor privacy review
  • AI resume templates + completed examples: AI Security Analyst and AI Governance & Risk Analyst
  • 3 AI career pathways + 35+ AI job titles: skills, frameworks, certs, bridge roles and a 90-day plan
  • Interview Question Bank: 105 questions with answer outlines, including 12 on AI security
  • Plus the full core Toolkit: 8 core projects, 8 role-specific resumes with completed examples, 100+ job titles, tracker and outreach templates
One-time · instant download

$39

AI Security Track + the complete Career Toolkit.

Get the ToolkitEverything inside
What to study

Free frameworks employers actually reference

ResourceWhat it isMost useful for
OWASP Top 10 for LLM Applications ↗The most common security risks in LLM apps: prompt injection, sensitive information disclosure, excessive agency and moreAI security, AppSec
MITRE ATLAS ↗Adversary tactics and techniques against AI systems, like ATT&CK for AIAI security, SOC, threat intel
NIST AI RMF ↗A voluntary framework for managing AI risk: Govern, Map, Measure, ManageAI governance, GRC
ISO/IEC 42001 ↗The international standard for an AI management systemAI governance, audit
NIST CSF 2.0 ↗The core cybersecurity framework most GRC work builds onEveryone

Cert details change. Always confirm on the vendor's site before you pay.

Questions

AI security careers, answered

Do I need to know how to code or build AI models?

Not for most of these roles. AI governance and privacy work is mostly analysis, writing and judgment. The technical AI security path benefits from some scripting and AppSec knowledge, but you don't need to train models. You need to understand how AI systems fail and how to control them.

Can I get an AI security job with no experience?

Rarely as a very first job. The realistic route is a first role in SOC, GRC, AppSec or cloud while you build AI projects on the side. Many teams are adding AI work to existing security roles, so the person who already has AI projects is the obvious choice.

Which certification should I get first?

A security foundation first (Security+ or ISC2 CC). Then CompTIA SecAI+ for the technical path or IAPP AIGP for governance. Projects matter more than a second cert at this stage.

Will AI replace entry-level security jobs?

AI is changing the work. It helps with summarizing alerts, writing queries and reducing busywork. It's also creating new risks that need people to test, govern and respond to them. Learning to secure and govern AI is one of the best ways to stay valuable as the field changes.