AI Cyber Security Engineer

Cyber Security Consulting

• Conduct cyber security assessments across technology estates, cloud environments, applications, networks, identity platforms and operational processes.
• Review security architectures and provide pragmatic recommendations aligned to business risk.
• Support the design and implementation of security controls across areas such as access management, data protection, logging and monitoring, vulnerability management, incident response and third-party risk.
• Help clients interpret security requirements, assess control maturity and develop actionable improvement roadmaps.
• Translate technical findings into clear, business-relevant advice for senior stakeholders.

AI and Agentic System Security

• Assess the security risks associated with AI-enabled applications, LLM integrations, AI agents, autonomous workflows and model-connected business processes.
• Review AI system designs for risks such as prompt injection, excessive agency, data leakage, insecure tool use, unsafe output handling, model supply chain exposure and weak human oversight.
• Support threat modelling for agentic systems, including how agents access tools, call APIs, retrieve data, make decisions and trigger actions.
• Advise on secure patterns for AI application development, including permission boundaries, identity controls, sandboxing, auditability, input/output validation and human-in-the-loop controls.
• Help clients establish governance and assurance processes for AI systems across the life cycle, from experimentation through to production deployment.

AI-Enabled Security Operations

• Identify opportunities to use AI safely to improve cyber security operations, such as alert triage, threat intelligence enrichment, incident summarisation, detection engineering, reporting, vulnerability prioritisation and control testing.
• Support the evaluation and adoption of AI-enabled security tools, ensuring appropriate security, privacy, governance and operational safeguards are in place.
• Help security teams design workflows where AI augments analysts without introducing unacceptable risk, over-reliance or loss of accountability.
• Develop practical playbooks, guardrails and operating models for the responsible use of AI within SOC, GRC, vulnerability management and incident response functions.
• Work with clients to measure the effectiveness, limitations and risks of AI-assisted security processes.
• Even if you don't meet every requirement below, feel free to still apply as we are often hiring for similar roles which your background might be better suited to.

• Strong background in cyber security consulting, security architecture, risk management or security operations.
• Good understanding of common security domains, including identity and access management, cloud security, application security, data protection, vulnerability management, incident response and security monitoring.
• Ability to assess technical environments and produce clear, prioritised recommendations.
• Experience engaging with both technical teams and senior business stakeholders.
• Understanding of AI, generative AI or LLM-enabled systems, including how AI applications interact with data, prompts, APIs, tools and users.
• Awareness of emerging AI security risks such as prompt injection, sensitive information disclosure, excessive agency, insecure output handling, model/data poisoning, vector or embedding weaknesses and AI supply chain risk.
• Ability to perform threat modelling for complex systems, including AI-assisted or agentic workflows.
• Strong written and verbal communication skills, with the ability to explain emerging technical risks in simple, practical terms.

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