AI Architect (AI for Security)
Based in the United KingdomFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- AWSPythonLLM
Requirements
- Strong hands-on background in offensive security, including vulnerability research, penetration testing, and exploit development.
- Proven experience building or operating LLM-powered security automation systems or agentic AI pipelines.
- Deep understanding of exploit chaining, CVE analysis, and real-world threat intelligence workflows.
- Experience working with local and self-hosted LLMs, including performance tuning, quantization, and infrastructure trade-offs.
- Solid understanding of runtime security detection, anomaly detection, and incident response systems.
- Proficiency with cloud environments (AWS preferred), including secure sandboxing and isolated execution environments.
- Strong programming skills (Python and shell scripting) with the ability to build production-ready prototypes.
- Experience in client-facing or consulting environments, with the ability to communicate complex systems to senior stakeholders.
- Ability to operate independently as a domain expert in cross-functional, high-trust engagements.
- Strong analytical mindset with a balance of offensive security depth and AI systems understanding.
Responsibilities
- Participate in high-level technical sessions with security engineers to evaluate and challenge an existing AI-driven offensive security pipeline.
- Design and refine LLM-powered exploitation agents, including planning logic, tool use, sandbox orchestration, and execution safety.
- Optimize the performance and cost-efficiency of AI security workflows by benchmarking and comparing local and frontier models.
- Architect improvements to runtime anomaly detection systems, focusing on signal extraction, attack pattern identification, and actionable alerting.
- Define and implement automated response mechanisms for detected threats, including containment and remediation workflows.
- Build proof-of-concept solutions to validate architectural approaches and demonstrate measurable security improvements.
- Translate technical findings into structured recommendations, architecture roadmaps, and executive-ready presentations.
- Ensure all AI and data workflows comply with strict in-perimeter and regulated-environment constraints.
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