① Career Paths
① Career Paths
“Agentic AI Security” is not one job. It is a cluster of roles that emerged when systems stopped merely answering and started acting — calling tools, writing to memory, spawning sub-agents, and holding credentials of their own. Each role owns a different failure mode of that shift.
Do not pick a title first and then reverse-engineer the skills. Pick the failure you want to own. An engineer who wants to own “the agent called a destructive tool because a web page told it to” ends up in a very different day job from someone who wants to own “we cannot prove to an auditor which model version made this decision” — even though both roles are advertised as AI Security Engineer.
What this section covers
- The Five Core Roles — the roles with the clearest job descriptions and the most consistent hiring demand today.
- Adjacent Roles — AI Incident Response, MLSecOps, and AI Privacy Engineering: newer, less crowded, and often easier to enter.
- Choosing Your Entry Point — a decision guide based on the background you already have, plus the realistic ramp time from each starting point.
- What Employers Actually Screen For — how these roles are evaluated in practice, and which portfolio artifacts move a candidate from “interesting” to “interview”.
Security Engineer, Red Teamer, Orchestration Engineer, Architect, Governance Engineer
AI Incident Response, MLSecOps, AI Privacy Engineering
A decision guide by current background and realistic ramp time
How each role is evaluated, and which artifacts convert
The one-page summary
| # | Role | Core responsibility | Signature skills |
|---|---|---|---|
| 1 | Agentic AI Security Engineer | Vulnerability research, cloud security review, and automated log-analysis workflows | Python, Git, APIs, cloud, AI coding assistants |
| 2 | Agentic AI Red Teamer | Evaluating new attack vectors: prompt injection, memory poisoning, RAG attacks, jailbreaks | Adversarial ML, OWASP LLM Top 10, MITRE ATLAS |
| 3 | Agentic Security Orchestration Engineer | Designing safe multi-agent collaboration and tool exposure | MCP, LangGraph, event-driven design, containers |
| 4 | Agentic AI Security Architect | Trust boundaries, agent identity, data access policy, human-in-the-loop gates | Zero Trust, IAM, policy-as-code |
| 5 | AI Security Governance Engineer | Inventory, risk assessment, regulatory compliance, automated evidence collection | NIST AI RMF, EU AI Act, ISO/IEC 42001 |
Every one of these roles is easier to enter with a red teamer’s evidence than with a builder’s demo. Even the governance role: a risk register backed by logs you personally produced beats a risk register copied from a template. That is why the 90-Day Plan has you attack your own agents in month two, before you publish anything.
Next, work through the Skill Tree to see which layers each role demands — or jump straight to the Threat Landscape if you want the failure modes first.