AI/ML Security Engineer

• Design and develop frameworks to evaluate the security, safety, accuracy, reliability, and performance of ML/GenAI solutions
• Identify, reproduce, and remediate prompt injection and indirect prompt injection vulnerabilities
• Develop automated security and adversarial tests for LLMs and Agentic AI, including jailbreaks, data leakage, and unsafe tool use
• Build and maintain metrics, monitoring, and evaluation capabilities for AI/ML applications
• Collaborate with engineering and security teams to develop AI threat models, security controls, and guardrails
• Investigate vulnerabilities and unexpected behavior across LLMs, AI agents, APIs, and supporting infrastructure
• Contribute to AI/ML infrastructure, CI/CD pipelines, APIs, and automation
• Write scalable, secure, and maintainable code, primarily in Python
• Develop unit, integration, functional, and security tests
• Participate in code reviews, troubleshooting, production support, and security assessments
• Stay current with emerging AI security threats, attack techniques, and defensive strategies

• 4–5 years of experience in ML Engineering, Software Engineering, AI Security, Application Security, or a related field, or an advanced degree with relevant experience (preferred)
• Experience with Generative AI, LLMs, and/or Agentic AI (preferred)
• Understanding of LLM security threats, especially prompt injection, indirect prompt injection, jailbreaks, and data leakage (preferred)
• Experience with AI/ML security testing, adversarial testing, red teaming, vulnerability assessment, or threat modeling (preferred)
• Experience building AI/ML evaluation, monitoring, or governance frameworks (preferred)
• Strong Python programming skills; Java or other languages are a plus (preferred)
• Experience with ML deployment, CI/CD, data pipelines, and production infrastructure (preferred)
• Hands-on experience with AWS, Docker, and Kubernetes (preferred)
• Strong foundation in software engineering, APIs, distributed systems, databases, and testing (preferred)
• Experience with Git/GitHub and Agile/Sprint development environments (preferred)
• Strong debugging, analytical, and problem-solving skills (preferred)