Job Description & Details
This is a heavy-hitting hands-on technical leadership role where you will actually build and secure the next wave of AI architectures instead of just pushing paper or talking about policy. If you know your way around agentic frameworks and cloud security, this gives you a chance to tackle cutting-edge LLM vulnerabilities at scale in an enterprise environment.
What You'll Actually Be Doing
You'll spend your days designing and optimizing AI-specific architectures, threat models, and prevention workflows from scratch. Expect to work closely with data scientists to secure agentic and MCP architectures, wire up neural networks for risk scoring, and mentor junior engineers while making sure the tech stack doesn't leave the door wide open for novel exploits.
The Core Tech Stack
You absolutely must have deep hands-on expertise in Python, Java, C, or R, paired with at least five years in Azure or AWS cloud-native environments. Familiarity with agentic frameworks like LangChain, LangGraph, or Crew, alongside a solid grasp of compliance frameworks like NIST AI-RMF, ISO42001, and the OWASP Top 10 for LLMs, will be your bread and butter here.
Interview Expectations
They will likely grill you on how you secure agentic workflows against prompt injection and indirect data poisoning, so be ready to whiteboard specific mitigation strategies using Model Context Protocols. The hiring manager is secretly looking to see if you can balance high-level architectural governance with low-level code review without slowing down feature delivery.
Application Advice
Make sure your resume calls out exact metrics around your cloud security deployments and clearly highlights your experience with agentic frameworks and LLM threat modeling. Weave in keywords like NIST AI-RMF, OWASP Top 10 for LLM, and specific programming languages right at the top so you easily clear the initial ATS filters.