Your influential mission. You will...
- 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 (Including Vibe Coded Applications).
- 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)
Components for success. You...
- Hold valid and relevant Certifications or equivalent, verifiable experience in the field of Cyber Security and/or Information Technology.
- Bring solid infrastructure and security engineering experience — Linux, networking, cloud, IAM, container security and automation.
- Know your way around both self-hosted LLM deployment and cloud LLM platforms (e.g. Azure Foundry, Amazon Bedrock, Google VertexAI, Ollama, LMStudio etc).
- Can review and assess AI systems against best practice and clearly advise teams on what to harden, improve, or remediate on an ongoing basis.
- 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.
- 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.
- Have prior experience in guardrail implementation and design evaluation, including prompt-injection defense, output validation, and hallucination mitigation.
- Had exposure to using infrastructure-as-code (Terraform, Ansible) and CI/CD pipelines to make controls repeatable.
- Have experience navigating, and working in regulated environments such as gaming, finance, or healthcare.
- Have clear communication, presentation and collaboration skills — strong documentation skills and cross-team collaboration are central to this role.
You'll get extra points for...
- Hands-on experience building CI/CD security gates and guardrails — the role advises on these more than builds them, but practical experience helps you guide teams well.
- Working knowledge of Python and Bash scripting is an advantage, any other development languages are also a bonus.
- Hands-on experience securing MCP / agentic AI infrastructure and the governance of these tools.
- Hands-on experience with AI Enablement and optimizing workflows using agentic AI and “Vibe coding”.
- Familiarity with AIBOM / SBOM tooling (e.g. OWASP Dependency-Track, and the CycloneDX SBOM Standard used) and supply-chain security.
- Exposure to MLSecOps practices and AI red-teaming.
- Relevant certifications across cloud or emerging AI-security credentials.
Thrive in a culture that values...
- Collaboration across teams
- Ownership, curiosity, and a proactive approach to solving complex security challenges
- Continuous learning and the opportunity to grow into the role while working on AI security topics that are becoming increasingly important for the business.
- Practical impact, with the chance to help shape Playtech’s AI future and support secure AI adoption across the company.
SYSTEM SECURITY TEAM
You will be part of the System Security - Endpoint & Gateway team, collaborating closely with another System Security team focused on Data & Identity Security. You will work with team members including an AI Security Engineer focused on Workforce AI, System Security Engineers, and a Principal Security Engineer, while also collaborating with the Playtech AI Committee, other Playtech Security teams, the Application Security Team, and teams across the wider business.
Playtech is an equal opportunities employer. Our mission is to welcome everyone and create inclusive teams. We celebrate differences and encourage everyone to join us and be themselves at work.