About the role

Position: AI/ML Security Engineer – GenAI & Prompt Injection
Engagement Mode: contract
Location: remote

Position Overview:
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 at Workiva. 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. This role
requires strong programming skills, a solid foundation in software engineering, and hands-on experience
with AI/ML security testing and adversarial techniques.

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