AI/ML Security Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked just now — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 17h ago
The date the source published, not the day we noticed it (2026-10-13). Last seen at its source just now.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
Mexico, United States, Costa Rica, Honduras
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $4,238–7,062/mo
Middle 50% of 16 listings that do state pay — Engineering · all levels · Mexico · USD/month. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Workable employer's own board first seen 1h ago · last seen just now
The listing
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.
Key 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
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 (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)
Benefits
- 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)