AI Security Engineer
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Function
The AI Security Engineer builds in security over the entire AI lifecycle. It protects AI solutions, models, agents, data, and integrations while helping to apply AI responsibly for detection, analysis, vulnerability management, patch prioritization, and secure development. Human responsibility and control remain the starting point.
Responsibilities include:
• Conducting threat modeling, risk, and security assessments for GenAI, ML, and agentic AI solutions.
• Develop guardrails for identity, least privilege, secrets, network isolation, data and prompt security, tool use, output validation, logging and monitoring.
• Test abuse scenarios, including prompt injection, unwanted data exfiltration, excessive privileges, unreliable output, and abuse of tools or agents.
• Integrate security requirements into sandboxes, gateways, pipelines, model and dependency management, and production platforms.
• Help design security monitoring and incident response for AI components, including ownership, audit trails, and escalation.
• Assessing suppliers, models, libraries and external AI services as part of the supply chain risk.
Technical competencies
• Proven experience in cybersecurity engineering, cloud security, application security, IAM, SOC or DevSecOps.
• Insight into specific risks of LLMs, agents, retrieval, model and data supply chains.
• Experience with security testing, technical risk assessments and translating findings into actionable measures.
• Ability to enable innovation with proportional controls, without reducing security to a checklist.
• Knowledge of GDPR, AI Act, NIS2 or similar frameworks.
• Knowledge of the public sector, G-Cloud or OISZ context is an asset.
Generic competencies
• Innovation: You follow the latest trends and experiment with innovative AI technologies.
• Problem-solving skills: You analyze complex issues and translate them into pragmatic solutions.
• Collaboration: You work smoothly with colleagues from different disciplines (IT, business, security, architecture).
• Communication: You can clearly explain technical concepts to both technical and non-technical stakeholders.
• Advising: You are strong in structuring, visualizing, advising and guiding multidisciplinary decision-making.
• Result orientation: You monitor deadlines and ensure quality deliveries
Skills
- AI-securityrisico’s: LLM’s, agents, retrieval en model- en datasupply chains.
- Experience in integrating security measures into software development and cloud platforms.
- Knowledge of GDPR, AI Act, NIS2 or similar frameworks.
- Security engineering: cybersecurity, cloud, applicaties, IAM, SOC of DevSecOps.
- Translating security testing and technical risk analyses into actionable measures.
Languages
Dutch - Level Active knowledge
English
French - Level Active knowledge
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