AI/ML Security Engineer

CrewBloom

. Design and develop frameworks to evaluate the security, safety, accuracy, reliability, and performance of ML/GenAI solutions .

Posted 10/14/2026full-timeRemote • Mexico, United States, Costa Rica, HondurasMid-LevelSenior💰 $35 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and evaluating security frameworks for AI/ML solutions, with a strong focus on prompt injection vulnerabilities and adversarial testing. Proficient in Python programming and familiar with CI/CD pipelines, cloud infrastructure, and security assessments.

Highest-signal resume keywords

Python ProgrammingAI/ML Security TestingGenerative AI ExperienceAWS, Docker, KubernetesVulnerability Assessment

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ML EngineeringSoftware EngineeringApplication SecurityAdversarial TestingThreat ModelingData LeakageJailbreaksUnit TestingIntegration TestingFunctional Testing

Soft Skills

Analytical SkillsProblem-Solving SkillsDebugging Skills

Tools & Technologies

Git/GitHubCI/CD PipelinesAPIsDistributed SystemsMonitoring Tools

Industry Keywords

AI SecurityML DeploymentEvaluation FrameworksSecurity AssessmentsAgile Development

Tech Stack

Tools & technologies

AWSDistributed SystemsDockerJavaKubernetesPython

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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)