AI Security Engineer - LLM & GenAI Security

Pauwels Consulting
Brussel, Belgium
1 day ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience required
1 year minimum
Working hours
Regular working hours
Languages
Dutch, English, French
Job source

Tech stack

Artificial Intelligence Cloud Computing Cloud Computing Security Cyber Security Identity and Access Management Role-Based Access Control Software Engineering Systems Integration Large Language Models Agentic-AI AI Platforms Devsecops

Job description

  • Perform threat modeling, risk assessments, and security evaluations for GenAI, ML, and agentic AI solutions.
  • Develop security guardrails for identity management, least privilege, data protection, and prompt security.
  • Test for abuse scenarios such as prompt injection, data exfiltration, and unauthorized tool usage.
  • Integrate security requirements into sandboxes, gateways, CI/CD pipelines, and production platforms.
  • Design security monitoring and incident response protocols specifically for AI components.
  • Evaluate the supply chain risk of vendors, models, libraries, and external AI services.

Requirements

  • You have 3+ years of experience in security engineering covering cybersecurity, cloud security, IAM, or DevSecOps.
  • You possess 3+ years of experience integrating security controls within software development pipelines and cloud platforms.
  • You bring 1+ years of experience identifying security risks associated with LLMs, agents, and model supply chains.
  • You have 1+ years of experience conducting technical security testing and risk assessments.
  • You possess 1+ years of knowledge regarding GDPR, AI Act, or NIS2 frameworks.
  • You’re proactive and solution-oriented with strong analytical and communication skills.
  • You have active knowledge of Dutch OR French (with good understanding of the other language), and English.

Nice to Haves

  • Experience within the public sector or the G-Cloud environment.
  • Ability to translate technical findings into actionable measures for non-technical stakeholders.

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