Key Skills: Security Engineering, Threat Modeling, Python, AI/ML, Terraform, CloudFormation, Penetration Testing, MITRE ATLAS, OWASP, Infrastructure as Code
Good to Have Skills: Expertise in AI red teaming exercises, experience with specialized AI security tools like PyRIT and Garak, custom LLM evaluation harnesses, contributions to AI security or open-source security projects, and experience with enterprise-level security solutions for generative AI and ML systems.
Roles & Responsibilities:
- Develop and enhance security strategies, red teaming programs, and solution designs while troubleshooting technical issues and creating scalable solutions.
- Design secure, high-quality AI and software architectures, reviewing and challenging designs and code to ensure adversarial resilience.
- Reduce AI and LLM security vulnerabilities by adhering to industry standards and emerging AI safety research, evolving policies, testing protocols, and controls.
- Collaborate with stakeholders across product, data science, cyber, legal, and risk to understand AI use cases and recommend modifications during periods of heightened vulnerability.
- Conduct discovery, threat modeling, and adversarial testing on generative AI, RAG pipelines, and ML systems to identify vulnerabilities such as prompt injection and jailbreaking.
- Define and implement AI red teaming methodologies, playbooks, and success metrics, establishing mechanisms for continuous testing and safe rollout of new AI models.
- Collaborate within a cross-functional team to develop relationships, influence senior stakeholders, and drive alignment on AI risk tolerance and mitigation priorities.
Experience Required: Formal training or certification on security engineering concepts and 3+ years applied experience required