We are looking for an AI Security Engineer for a Tier One Consultancy who are working on a large security programme for a prestgious Financial Services end customer.
The individual will expand the product roadmap, strengthen the organisation’s security posture, and ensure proactive identification, mitigation, and response to risks associated with both traditional data systems and emerging GenAI technologies.
This position requires a combination of hands-on engineering expertise and deep knowledge of Data Security, AI Security, and cloud-native security practices. The role will leverage insights from enterprise security controls including Data Loss Prevention (DLP), Data Privacy and Protection, GenAI-specific controls, Security Information and Event Management (SIEM), and vulnerability management frameworks.
Primary Responsibilities
The individual will expand the product roadmap, strengthen the organisation’s security posture, and ensure proactive identification, mitigation, and response to risks associated with both traditional data systems and emerging GenAI technologies.
This position requires a combination of hands-on engineering expertise and deep knowledge of Data Security, AI Security, and cloud-native security practices. The role will leverage insights from enterprise security controls including Data Loss Prevention (DLP), Data Privacy and Protection, GenAI-specific controls, Security Information and Event Management (SIEM), and vulnerability management frameworks.
Primary Responsibilities
- Drive enhancements to the AI/GenAI security platform and scanning infrastructure, ensuring alignment with strategic objectives and approved budgets.
- Collaborate with engineering teams to design, build, and optimise cloud-native Data & GenAI Security services.
- Support stakeholders in leveraging and adopting modern Data & GenAI Security cloud-native application architectures.
- Ensure Data Security architecture and cloud infrastructure align with current security standards and secure software lifecycle best practices.
- Proven experience conducting threat modelling, penetration testing, and vulnerability assessments across AI/ML ecosystems, including data pipelines, model APIs, and supporting infrastructure.
- Hands-on expertise with core cybersecurity technologies, including firewalls, SIEM platforms, IDS/IPS, and related security tooling.
- Strong proficiency in Python, with demonstrated ability to develop automation scripts, security tooling, and data-driven solutions.
- Deep understanding of secure software development practices, including OWASP principles and DevSecOps methodologies integrated within CI/CD workflows.
- Experience securing cloud and AI workloads on major cloud platforms such as AWS and Azure.
- Working knowledge of machine learning concepts, data processing techniques, and common AI/ML frameworks (e.g., PyTorch, Scikit-learn, LangChain) is considered a strong advantage.
