AI Security Engineer

• Minimum 7-10 years of experience in a hands-on security architecture and engineering role within an agile SaaS development organization
• Demonstrated ability to lead cross-functional security initiatives in an agile SaaS development organization
• Strong foundation and experience across core AppSec domains
• Direct, practical, end-to-end experience across the following
• Security architecture and implementation for microservice, cloud-native, and serverless application architectures
• GitOps implementation, security, and utilization
• Development of security tooling and automation, delivered as software
• Continuous security and compliance
• Recent hands-on exposure to securing AI/ML environments
• Working familiarity with AI/ML security risks and frameworks — OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, EU AI Act. You don't need to have lived in these for years; you need to understand what they're solving for
• Awareness of agentic AI architectures and the risks associated with them — autonomous agents, tool orchestration, memory systems, multi-agent coordination 

Preferred

• We understand that AI security is an emerging discipline. These aren't just checkboxes—they’re indicators that you have actively been engaging with this space.
• Direct experience in LLM security, model red-teaming, or AI threat modeling
• Hands-on experience securing agentic AI systems (e.g., LangChain, AutoGen, CrewAI, or similar frameworks)
• Experience contributing to or implementing AI governance programs, risk registers, or responsible AI policies
• Experience with security incident response in AI/ML environments with AI/ML workloads
• Familiarity with AI governance principles: model transparency, explainability, bias/fairness considerations, and data lineage
• Relevant certifications, for example ISC2 (AI Security, CISSP, CCSP, CSSLP, ISSAP, ISSEP)