About this role
The AI/ML Security Engineer will help develop frameworks, tools, and infrastructure to evaluate, secure, monitor, and govern Machine Learning, Generative AI, and Agentic AI solutions. A key focus of this role is identifying and remediating AI security threats, particularly prompt injection, jailbreaks, data leakage, adversarial inputs, and unsafe AI/agent behavior. The engineer will work closely with AI/ML, security, and product teams to build automated security evaluations, establish security metrics, investigate vulnerabilities, and implement effective remediation and guardrails across the AI/ML lifecycle.
Key Responsibilities:
- Design and develop frameworks for evaluating 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 using 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.
Required Skills:
- 6–7 years of experience in ML Engineering, Software Engineering, AI Security, Application Security, or a related field.
- Experience with Generative AI, LLMs, and/or Agentic AI.
- Understanding of LLM security threats including prompt injection, indirect prompt injection, jailbreaks, and data leakage.
- Strong programming skills in Python.
- Strong foundation in software engineering, APIs, distributed systems, databases, and testing.
- Experience with Git/GitHub and Agile/Sprint development environments.
- Strong debugging, analytical, and problem-solving skills.
Preferred (Bonus) Skills:
- Experience with AI/ML security testing, adversarial testing, red teaming, vulnerability assessment, or threat modeling.
- Experience building AI/ML evaluation, monitoring, or governance frameworks.
- Java or other programming languages.
- Experience with ML deployment, CI/CD, data pipelines, and production infrastructure.
- Hands-on experience with AWS, Docker, and Kubernetes.
- Advanced degree with relevant experience.
What we offer:
The team provides a dynamic work environment that fosters innovation and professional growth, along with opportunities to work on cutting-edge AI technologies.