Related skills
devsecops threat modeling llms vector databases rag architectures📋 Description
- Design and evolve enterprise AI security architectures across AI, GenAI, ML platforms
- Define security strategy and reference architectures for AI systems
- Advise engineering on secure design, threat mitigation, risk acceptance
- Implement advanced security controls for LLMs, agentic frameworks, and AI APIs
- Lead threat modeling, red-teaming, and adversarial testing for AI systems
- Drive secure AI lifecycle across development, training, deployment, runtime
🎯 Requirements
- Bachelor's degree in CS, AI, Cybersecurity or related field
- 8-12 years in security engineering with AI/ML platforms
- Deep understanding of application and cloud security and threat modeling
- Experience securing large-scale distributed systems, microservices, APIs
- Expertise in AI/ML security: LLMs, RAG, vector databases, agentic frameworks
- DevSecOps, automation, and secure SDLC integration
🎁 Benefits
- 25 days annual leave plus extra days
- Holiday buy/sell up to 5 days
- Hybrid/flexible working
- Health Insurance
- Pension Contribution
- Educational Assistance Program
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