AI Security Engineer (System Security)
Playtech's System Security team is looking for a proactive AI Security Engineer (System Security) to help secure how AI systems are designed, built, and operated across both on-premise and cloud environments. In this role, the focus will mainly be on infrastructure security, while also working closely with teams across development, security, and AI adoption. The ideal candidate will have hands-on experience securing or administering the platforms behind AI and agentic workloads, including containerization, virtualization, CI/CD pipelines, and related technologies. Playtech is looking for someone collaborative, proactive, and curious, with a strong sense of ownership and a continuous learning mindset. This is a great opportunity to contribute to Playtech’s AI security journey and help shape how AI is adopted securely across the business.
- Review the AI systems and infrastructure, including local and cloud LLM deployments, gateways, vector stores, and agentic / MCP components, and provide clear recommendations on required hardening measures and areas for improvement.
- Assess existing guardrails and controls, such as input/output filtering, prompt-injection defenses, rate limiting, and authentication, against industry best practice, provide recommendations to strengthen their effectiveness and drive the implementation of improvements and new controls to ensure the secure and responsible use of AI.
- Advise on secure-by-design AI architecture, reviewing team designs and deployments against recognized frameworks (OWASP, MITRE ATLAS, NIST AI RMF, ISO/IEC 42001).
- Recommend and prioritize hardening across the infrastructure behind self-hosted and cloud-based LLMs, and guide teams through remediation.
- Evaluate the AI supply chain, such as model provenance, AIBOM/SBOM, dependency and artifact scanning, and provide recommendations to address gaps.
- Define standards, reference patterns, and best-practice guidance to ensure teams across Playtech build and operate AI securely.
- Review logging, observability, and detection coverage for AI workloads mapped to frameworks such as MITRE ATLAS, and recommend enhancements to ensure the SOC can effectively monitor and respond across the full AI attack surface.
- Assess identity, access, and secrets management for models, tools, and data, advising on least-privilege improvements.
- Support compliance in a regulated environment with audit-ready assessments, evidence, and documentation.
- Drive innovation within the team - Investigate and where possible implement Agentic AI usage within the unit, to optimize time consuming activities (Chatbots, automation with Hermes or n8n etc).
- Hold valid and relevant Certifications or equivalent, verifiable experience in the field of Cyber Security and/or Information Technology (required).
- Bring solid infrastructure and security engineering experience - Linux, networking, cloud, IAM, container security and automation (required).
- Know your way around both self-hosted LLM deployment and cloud LLM platforms (e.g. Azure Foundry, Amazon Bedrock, Google VertexAI, Ollama, LMStudio etc) (required).
- Can review and assess AI systems against best practice and clearly advise teams on what to harden, improve, or remediate on an ongoing basis (required).
- Have prior knowledge of LLM-specific threats: prompt injection, sensitive-data disclosure, data/model poisoning, excessive agency, insecure output handling, supply-chain risk and how to mitigate them (required).
- Have knowledge of some of the various AI security frameworks and Guidelines - OWASP Top 10 for LLM Applications (2025) and for Agentic Applications (2026), MITRE ATLAS, NIST AI RMF, ISO/IEC 42001, CISA/NSA guidance, and the EU AI Act - and how to translate them into controls (required).
- Have prior experience in guardrail implementation and design evaluation, including prompt-injection defense, output validation, and hallucination mitigation (required).
- Had exposure to using infrastructure-as-code (Terraform, Ansible) and CI/CD pipelines to make controls repeatable (required).
- Have experience navigating, and working in regulated environments such as gaming, finance, or healthcare (required).
- Have clear communication, presentation and collaboration skills - strong documentation skills and cross-team collaboration are central to this role (required).
- Hands-on experience building CI/CD security gates and guardrails (nice-to-have).
- Working knowledge of Python and Bash scripting is an advantage, any other development languages are also a bonus (nice-to-have).
- Hands-on experience securing MCP / agentic AI infrastructure and the governance of these tools (nice-to-have).
- Hands-on experience with AI Enablement and optimizing workflows using agentic AI and “Vibe coding” (nice-to-have).
- Familiarity with AIBOM / SBOM tooling (e.g. OWASP Dependency-Track, and the CycloneDX SBOM Standard used) and supply-chain security (nice-to-have).
- Exposure to MLSecOps practices and AI red-teaming (nice-to-have).
- Relevant certifications across cloud or emerging AI-security credentials (nice-to-have).
Playtech plc is one of the world's largest gambling technology companies, providing software, platforms and content to online and land-based operators. Founded in 1999 and registered in the Isle of Man, it supplies casino, live casino, sportsbook, bingo and poker products, along with its IMS player-management platform. The company also runs B2C operations, most notably the Snaitech business in Italy. Listed on the London Stock Exchange, Playtech employs thousands of people across offices worldwide.