security engineer in iGaming

Playtech is a gaming technology company focused on regulated and regulating markets across its B2B business. It delivers software, services, content, business intelligence, and platform technology to support safe, engaging, and entertaining gaming experiences.

• Review AI systems and infrastructure, including local and cloud LLM deployments, gateways, vector stores, and agentic/MCP components, and recommend hardening measures;
• Assess guardrails and controls such as input/output filtering, prompt-injection defenses, rate limiting, and authentication, and drive improvements and new controls;
• Advise on secure-by-design AI architecture against OWASP, MITRE ATLAS, NIST AI RMF, and ISO/IEC 42001;
• Recommend and prioritize hardening across infrastructure behind self-hosted and cloud-based LLMs, and guide teams through remediation;
• Evaluate the AI supply chain, including model provenance, AIBOM/SBOM, dependency and artifact scanning, and recommend ways to address gaps;
• Define standards, reference patterns, and best-practice guidance for secure AI development and operations;
• Review logging, observability, and detection coverage for AI workloads mapped to MITRE ATLAS, and recommend enhancements;
• Assess identity, access, and secrets management for models, tools, and data, and advise on least-privilege improvements;
• Support compliance through audit-ready assessments, evidence, and documentation;
• Investigate and, where possible, implement Agentic AI usage within the unit to optimize time-consuming activities;
• Collaborate with System Security, Data & Identity Security, AI, Application Security, and wider business teams.

• Hold valid and relevant Cyber Security and/or Information Technology certifications or equivalent verifiable experience;
• Have solid infrastructure and security engineering experience with Linux, networking, cloud, IAM, container security, and automation;
• Know self-hosted LLM deployment and cloud LLM platforms such as Azure Foundry, Amazon Bedrock, Google VertexAI, Ollama, and LMStudio;
• Be able to review AI systems against best practices and advise teams on hardening, improvement, and remediation;
• Know LLM-specific threats including prompt injection, sensitive-data disclosure, data/model poisoning, excessive agency, insecure output handling, and supply-chain risk;
• Know AI security frameworks and guidelines including OWASP Top 10 for LLM Applications, OWASP Top 10 for Agentic Applications, MITRE ATLAS, NIST AI RMF, ISO/IEC 42001, CISA/NSA guidance, and the EU AI Act;
• Have experience with guardrail implementation and design evaluation, including prompt-injection defense, output validation, and hallucination mitigation;
• Have exposure to infrastructure-as-code with Terraform or Ansible and CI/CD pipelines;
• Have experience working in regulated environments such as gaming, finance, or healthcare;
• Have clear communication, presentation, documentation, and cross-team collaboration skills;
• Nice to have: CI/CD security gates and guardrails, Python and Bash scripting, other development languages, MCP/agentic AI infrastructure security and governance, AI Enablement and workflow optimization with agentic AI and Vibe coding, AIBOM/SBOM tooling, supply-chain security, MLSecOps, AI red-teaming, cloud or emerging AI-security certifications.

• No conditions specified