AI Security - Forward Deployment Engineer

This is a heavy-hitting AI Security Forward Deployment role sitting at the intersection of agentic workflows, DevSecOps pipelines, and enterprise-grade security products. You'll be bridging the gap between cutting-edge LLMs and robust infrastructure to ensure secure development lifecycles.

What You'll Actually Be Doing

You'll spend your days evaluating next-gen security products, integrating AI model scanners into CI/CD pipelines, and collaborating with architects and vendors to secure complex cloud environments. Expect to juggle vendor roadmaps while hands-on designing and deploying agentic systems that actively scan AI models and engines for vulnerabilities.

The Core Tech Stack

You need absolute fluency in Python and JavaScript/TypeScript, paired with deep Kubernetes and cloud-native container ecosystem experience. But what really sets this role apart is the mandatory Agentic AI capability—you must know how to design and develop agents, host MCP Servers, build agent looping mechanisms, and manage spec-driven development alongside traditional security tools and Linux/Windows server environments.

Interview Expectations

Expect to be grilled on how you architect secure, agentic loops and prevent prompt injection or unintended data leakage within automated AI workflows. The hiring manager is secretly looking for deep systems-level thinking combined with practical security paranoia, wanting to know not just how to build cool agentic features, but how they break and how you lock them down.

Application Advice

Make sure your resume screams 'Agentic AI' and 'DevSecOps' right at the top, explicitly detailing your experience with LLMs, MCP servers, and Kubernetes security integrations. Don't hide your Python or TypeScript background; put front and center any specific projects where you tied APIs together, handled SSO/SAML, or built autonomous workflows to sail smoothly past the initial ATS filters.