System & AI Security Engineer

About the role

Playtech, a London-listed gaming technology company founded in 1999, is looking for a proactive System and AI Security Engineer to join its System Security team. The role focuses on infrastructure security (EDR, email security gateways, endpoint hardening) and plays a part in the company's secure AI adoption, working closely with development, security and teams adopting AI. Hands-on experience securing and administering platforms supporting AI and agentic workloads is essential.

Key responsibilities

• Review AI systems and infrastructure (local and cloud LLM deployments, gateways, vector stores, agentic / MCP components) and recommend hardening measures.
• Design, implement, support and improve EDR, proxy, email security and endpoint hardening.
• Support security risk assessments, audits and compliance reviews, and assess guardrails such as input/output filtering, prompt-injection defence, rate limiting and authentication.
• Recommend hardening for self-hosted and cloud-based LLMs and guide teams through remediation.
• Evaluate the AI supply chain (model provenance, AIBOM/SBOM, dependency and artifact scanning) and define standards and best-practice guidance for secure AI development.
• Review logging, observability and detection coverage for AI workloads (MITRE ATLAS) and assess identity, access and secrets management.
• Support compliance in a regulated environment and investigate and implement agentic AI usage (chatbots, automation with Hermes or n8n) to save time.

Required profile

• Valid and relevant cybersecurity or IT certifications or equivalent verifiable experience.
• Experience with EDR solutions (Defender for Endpoint, CrowdStrike, SentinelOne) and email security solutions.
• Solid infrastructure and security engineering experience (Linux, networking, cloud, IAM, container security, system hardening).
• Prior knowledge of LLM-specific threats and of frameworks such as OWASP Top 10 for LLM Applications, MITRE ATLAS, NIST AI RMF, ISO/IEC 42001, CISA/NSA guidance and the EU AI Act.
• Experience with guardrail implementation, infrastructure-as-code (Terraform, Ansible) and CI/CD pipelines.
• Experience in regulated environments such as gaming, finance or healthcare.

Required skills

• Self-hosted and cloud LLM platforms (Azure Foundry, Amazon Bedrock, Google VertexAI, Ollama, LMStudio)
• Knowledge of AI security frameworks and guidelines
• CI/CD security gates and guardrails; Python and Bash scripting are an advantage
• AIBOM / SBOM tooling (OWASP Dependency-Track, CycloneDX) and MCP / agentic AI infrastructure are a bonus