Job Description & Details
This is a hands-on cybersecurity engineering role based out of Dallas that blends traditional vulnerability management, secure SDLC enforcement, and bleeding-edge AI/LLM security. If you are tired of pure paperwork compliance and want to actually build detection workflows, threat model enterprise apps, and secure LLM deployments, this gig gives you the ownership to do so.
What You'll Actually Be Doing
Expect to spend your days knee-deep in risk-based vulnerability triage, tracking remediation across complex cloud and production environments, and coordinating security incidents. Beyond standard SOC and patching duties, you'll be actively shaping how the business securely adopts generative AI tools like GPT, Gemini, and Llama without opening the door to prompt injection or data leakage. You will write automation scripts in Python to streamline scanning and reporting, while collaborating with software engineering teams to embed security controls natively into the SDLC.
The Core Tech Stack
You absolutely need a solid grasp of vulnerability management platforms, threat detection tooling, and secure coding practices. Python is non-negotiable here for building automation and remediation scripts. On top of standard application security risks like SSRF, injection, and broken access control, you will need working knowledge of AI/LLM security primitives, guardrails, and adversarial red-teaming. If you've spent time building or auditing large-scale production applications, you'll feel right at home.
Interview Expectations
Expect the hiring team to grill you on handling a complex, multi-layered vulnerability incident under pressure, testing your ability to prioritize risk versus business velocity. They will likely present a scenario involving a direct prompt injection vulnerability in an enterprise LLM integration and ask you to walk through your threat modeling, red-teaming, and guardrail implementation strategy from scratch.
Application Advice
Make sure your resume leans heavily into concrete examples of Python automation for security workflows and real-world vulnerability triage. Don't just list buzzwords; highlight instances where you successfully managed risk across hosted production environments or implemented secure coding practices within an SDLC framework. If you have any exposure to AI security or open-source security tool contributions, put those right at the top.