Senior Manager - AI security Architect Guardrail Engineering

• Hands-on development experience with the ability to write and ship production Python, with TypeScript or Go experience preferred.
• Direct experience integrating or extending at least two AI security tools such as Garak, PyRIT, LLM Guard, Presidio, NeMo Guardrails, Lakera Guard, or equivalent tools.
• Practical experience executing prompt injection, indirect prompt injection, and jailbreak attacks against real LLM applications in red team, research, or CTF environments.
• Experience with RAG pipeline security, including retrieval-based data exfiltration, embedding inversion, vector store poisoning, and related defense patterns.
• Experience with agentic system adversarial testing, including agent loop hijacking, tool abuse, and privilege escalation in multi-agent orchestration frameworks.
• Solid understanding of OWASP LLM Top 10 and MITRE ATLAS, with the ability to map TTPs to concrete adversarial test cases.
• Experience integrating security into CI/CD pipelines such as GitHub Actions, Azure DevOps, or Jenkins by building security pipeline stages.
• A strong sense of ownership, desire to create meaningful outcomes, and passion for work that serves a greater good for customers, communities, or global challenges.
• Experience developing SIEM detection logic for AI workloads, including Sigma rules, KQL, or SPL queries for AI-specific anomaly detection.
• IaC security experience, including writing or reviewing Terraform or Bicep modules with security controls encoded.

10+ years of experience in Security Engineering or Application Security, including 3+ years in AI/ML Security, AI Red Teaming, or AI Security Tool Development; production-level Python development; hands-on integration or extension of at least two AI security tools such as Garak, PyRIT, LLM Guard, Presidio, NeMo Guardrails, or Lakera Guard; practical experience with prompt injection, indirect prompt injection, and jailbreak attacks; RAG pipeline security, including data exfiltration, embedding inversion, and vector store poisoning; adversarial testing of agentic AI systems, including tool abuse and privilege escalation; strong knowledge of OWASP LLM Top 10 and MITRE ATLAS; and experience integrating security testing stages into CI/CD pipelines using GitHub Actions, Azure DevOps, or Jenkins.

• Experience developing AI-specific SIEM detection rules using Sigma, KQL, or SPL.
• Terraform or Bicep security modules.
• Hands-on knowledge of LangChain, LangGraph, LlamaIndex, or Semantic Kernel.
• AI security research, publications, CVE disclosures, or conference presentations.
• Enterprise security engineering or red-team experience.
• The ability to communicate adversarial findings to senior stakeholders and collaborate with development teams to implement security mitigations.