About the Role
The role will be responsible for supporting the design and implementation of AI-enabled capabilities across Checkout, ensuring AI technologies are deployed in a safe, governed, and resilient manner. The successful candidate will work closely with Engineering, Data Governance, GRC, and business teams to embed security into AI systems, assess AI-related risks, and help the organisation adopt AI securely at scale.
As a Cyber Security Engineer I, you will act as the bridge between cyber security and emerging AI technologies. You will help shape how Checkout secures AI tools, models, data pipelines, and supporting infrastructure, while also identifying opportunities to use AI to strengthen cyber defence capabilities.
This is a hands‑on role suited to someone who understands modern security engineering and has a strong interest in AI/ML technologies, LLMs, automation, and risk management.
Responsibilities
- Design and implement security controls for AI and machine learning solutions, including LLM-based applications, model integrations, and supporting cloud infrastructure.
- Assess the security, privacy, and compliance risks associated with AI systems, including model misuse, prompt injection, data leakage, insecure plugins, over‑permissioned access, and third‑party AI services.
- Develop standards, guardrails, and reference architectures for the secure use of AI across the organisation.
- Review AI use cases, architectures, and deployments to ensure alignment with cyber security policies, regulatory requirements, and internal governance expectations.
- Build and maintain monitoring, detection, and response capabilities for AI‑related threats and misuse scenarios.
- Identify opportunities to use AI to enhance cyber security operations, such as alert triage, threat analysis, playbook automation, knowledge retrieval, and workflow optimisation.
- Stay current on evolving risks, attack techniques, regulations, and industry practices related to AI security and AI governance (inline with EU AI Act, ISO42001).
Qualifications
- Experience in cyber security engineering, security architecture, or a related security role.
- Strong understanding of core security domains such as identity and access management, cloud security, application security, data protection, logging and monitoring, and incident response.
- Knowledge of AI/ML and LLM concepts, including model deployment patterns, APIs, embeddings, vector stores, prompt handling, and common AI security risks.
- Experience securing cloud environments and modern development workflows in platforms such as AWS, Azure, or GCP.
- Familiarity with security risks relevant to AI systems, including prompt injection, data exfiltration, insecure model access, supply chain risks, model poisoning, and sensitive data exposure.
- Experience conducting architecture reviews, threat modelling, and security assessments for complex technical solutions.
- Ability to translate technical risk into clear, practical guidance for both engineering and non‑technical stakeholders.
- Strong collaboration skills and the ability to work across cyber security, engineering, data, legal, and business teams.
- A proactive mindset, with the ability to operate in a fast‑moving area where standards and best practices continue to evolve.
Benefits
- Hybrid working model with flexibility: three days per week in the office, remote work otherwise.
- Focus on professional growth and ownership from day one.
- Inclusive workplace that supports diversity and inclusion.
#J-18808-Ljbffr…