AI/ML Security Engineer

CrewBloom•North, SC

3d•Remote

About The Position

We are looking for an AI/ML Security Engineer with experience in prompt injection and AI security to join a remote team based in LATAM and working CST hours. You will help develop frameworks, tools, and infrastructure to evaluate, secure, monitor, and govern Machine Learning, Generative AI, and Agentic AI solutions. A key focus is identifying and remediating AI security threats, including prompt injection, jailbreaks, data leakage, adversarial inputs, and unsafe AI/agent behavior. You 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.

Requirements

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
Experience with Generative AI, LLMs, and/or Agentic AI
Understanding of LLM security threats, especially prompt injection, indirect prompt injection, jailbreaks, and data leakage
Experience with AI/ML security testing, adversarial testing, red teaming, vulnerability assessment, or threat modeling
Experience building AI/ML evaluation, monitoring, or governance frameworks
Strong Python programming skills; Java or other languages are a plus
Experience with ML deployment, CI/CD, data pipelines, and production infrastructure
Hands-on experience with AWS, Docker, and Kubernetes
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

Responsibilities

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