Career roadmaps / AI Security Engineer

AI Security Engineer

Secure applications built on large language models: find prompt injection, data leakage and unsafe tool use before attackers do.

One of the fastest-growing security specialisms as companies ship LLM features and agents.

Day to day

  • •Red-team LLM features before release
  • •Design guardrails and tool permissions
  • •Review agent architectures for data exposure
  • •Write findings engineers can act on

Start from: Some programming and basic security knowledge

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  1. 1

    Security and web foundations

    4–6 weeks

    Understand how web applications are attacked and defended.

    HTTP, APIs and authentication

    Every LLM feature is reached through an API; most real breaches start with auth mistakes.

    OWASP Top 10 for web

    The shared vocabulary for application risk that security reviews are written in.

    Python scripting

    Automating test cases and calling model APIs is daily work.

    Certifications

    • CompTIA Security+ · CompTIA

    Portfolio project

    Find and write up three vulnerabilities in a deliberately vulnerable web app, with reproduction steps and fixes.

  2. 2

    How LLM applications work

    3–4 weeks

    Build with model APIs so you understand what you will later attack.

    Prompting and system prompts

    Injection is an attack on instructions; you need to know how instructions are layered.

    Tool use and agents

    Tools turn a text bug into a real action like sending email or reading files.

    Retrieval-augmented generation

    Retrieved documents are an indirect injection path most teams overlook.

    Certifications

    • Claude Certified Associate – Foundations · AnthropicPractise

    Portfolio project

    Build a small RAG assistant with one tool, then document every place untrusted text enters the model.

  3. 3

    Attacking LLM applications

    4–6 weeks

    Run adversarial tests and turn results into evidence.

    OWASP Top 10 for LLM applications

    The reference list clients and auditors ask you to test against.

    Direct and indirect prompt injection

    The most common and most damaging LLM vulnerability class.

    Data exfiltration and system prompt leakage

    Leaked context is often the finding with the biggest business impact.

    Certifications

    No certification needed here. Your project is the proof.

    Portfolio project

    Red-team your own RAG assistant: a report with severity, evidence, and a regression test for each finding.

  4. 4

    Defence and architecture

    4 weeks

    Design systems that fail safely, and prove it.

    Least-privilege tool design

    Limiting what a tool can do caps the damage of any injection that succeeds.

    Human-in-the-loop controls

    Consequential actions need approval gates that attackers cannot talk their way past.

    Evaluation and regression testing

    A fix without a test comes back in the next release.

    Certifications

    • Claude Certified Architect – Foundations · AnthropicPractise

    Portfolio project

    Harden the assistant: permissions, approval gates and an eval suite that fails the build when an old attack works again.

  5. Finish line

    Prove you're ready to apply

    20 workplace scenarios. Reach 80% with no area below 60% for a job-ready signal.

    Take the readiness exam

Certification requirements, prices and exam formats change. Always confirm on the issuer's site, linked from the certifications page.

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