AI Security Engineer

Join Playtech as an AI Security Engineer to enhance the security of AI-powered applications. Collaborate with diverse teams to mitigate vulnerabilities and ensure safe gaming experiences. Founded in 1999, Playtech is a leading technology company in the gaming industry, focused on regulated markets. We deliver innovative products and services for a safe and engaging gaming experience. Learn more about us at Playtech People and Playtech.

• •Perform threat modelling and security design reviews for applications, focusing on AI and LLM-powered features.
• •Work closely with security, engineering, and data science teams to identify, analyze, and mitigate security vulnerabilities.
• •Review the security of AI application architecture, including RAG pipelines, agent and tool-calling flows, model APIs, and integrations.
• •Test AI features adversarially for prompt injection, data leakage, jailbreaks, and unsafe output handling.
• •Define guardrails, input and output validation, and monitoring for AI systems.
• •Help build secure-by-default patterns and guidance for safe AI feature shipping.
• •Support development using commercial and open-source security technologies.
• •Track the evolving AI threat landscape and translate it into practical standards for our teams.

• •Collaboration and teamwork to solve challenges.
• •Continuous development through mentorship, training, and hands-on experience.
• •Possibility to take ownership to improve security.
• •Diverse perspectives and backgrounds.

• •Have application security experience (secure code review, threat modelling, vulnerability management).
• •Have great written and spoken English.
• •Have higher education in IT or equivalent practical experience.
• •Understand how LLM and ML systems are built and deployed, and can reason about their failure modes.
• •Have experience with at least one programming language (Java, Python, JavaScript, etc.) and scripting ability.
• •Have great analytical skills and can find solutions to problems.
• •Are positive and proactive, and comfortable working across teams.

• •Familiarity with AI security frameworks such as the OWASP LLM Top 10, MITRE ATLAS, or NIST AI RMF.
• •Hands-on experience red-teaming AI models or AI-powered applications.
• •Experience with AI security or guardrail tooling.
• •Familiarity with security tools like Burp Suite, OWASP ZAP, SAST/DAST tools, or similar.
• •Knowledge of secure coding and design practices, and the secure software development lifecycle.
• •Understanding of data governance and privacy considerations in training and inference.