AI Security Engineer
New
T
The Quality Group (TQG)Sports nutrition
Germany, remoteFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- German and English
- Experience
- Several years
- Required Skills
- CI/CDLLMMLOpsGenerative AI
Requirements
- Degree in Computer Science, Cyber Security, Information Security, or a comparable qualification.
- Several years of experience in Security Engineering, Application Security, Cloud Security, or a related Cyber Security field.
- Hands-on experience with Generative AI, Large Language Models (LLMs), modern AI platforms, and cloud technologies (Azure, AWS, or Google Cloud).
- Experience with threat modeling, security assessments, architecture reviews, and modern DevSecOps, CI/CD, or MLOps practices.
- Strong analytical thinking and a security-first mindset.
- Effective communication skills for both technical and non-technical stakeholders.
- Fluent in German and English, both written and spoken.
- Knowledge of AI security frameworks such as OWASP Top 10 for LLM Applications, MITRE ATLAS, or NIST AI RMF is a plus.
- Experience with AI Red Teaming, RAG architectures, vector databases, or regulatory frameworks like ISO 27001, NIS2, and the EU AI Act is a plus.
Responsibilities
- Advise on and assess internally developed and externally sourced AI systems, Generative AI applications, LLM-based workflows, and agentic AI solutions from a security perspective.
- Conduct AI threat modeling, risk assessments, security reviews, and architecture assessments for software, cloud, and AI environments.
- Develop and implement Secure AI-by-Design and Security-by-Default principles and define security requirements for AI-powered systems.
- Identify and assess risks such as prompt injection, jailbreaking, data leakage, model poisoning, adversarial attacks, and insecure agent integrations, and develop appropriate mitigation strategies.
- Perform AI red teaming, technical security assessments, and reviews to strengthen the security of LLM platforms, agentic AI solutions, and AI service integrations.
- Build automated security controls and integrate AI security checks into DevSecOps, CI/CD, and MLOps processes.
- Establish monitoring and detection capabilities for AI applications and collaborate with Security Operations teams to investigate security events and abuse patterns.
- Advise engineering, product, and business teams on the secure use of AI and support the rollout of new AI solutions through training, standards, and best practices.
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