AI Security Engineer

This is a fully remote position, open to applicants in Ukraine.

📋 Description

• Evaluate AI systems and infrastructure, which includes local and cloud LLM deployments, gateways, vector stores, and agentic/MCP components, and offer precise recommendations for necessary hardening measures and areas needing enhancement.

• Examine existing guardrails and controls, such as input/output filtering, prompt-injection defenses, rate limiting, and authentication, in comparison to industry best practices, providing suggestions to enhance their effectiveness and facilitate the implementation of improvements and new controls for the secure and responsible use of AI.

• Offer guidance on secure-by-design AI architecture, analyzing team designs and deployments in relation to established frameworks (OWASP, MITRE ATLAS, NIST AI RMF, ISO/IEC 42001).

• Propose and prioritize hardening efforts across the infrastructure supporting self-hosted and cloud-based LLMs, while guiding teams through remediation processes.

• Assess the AI supply chain, including model provenance, AIBOM/SBOM, dependency, and artifact scanning, and recommend measures to address identified gaps (including Vibe Coded Applications).

• Establish standards, reference patterns, and best-practice guidance to ensure that teams across Playtech develop and operate AI securely.

• Analyze logging, observability, and detection coverage for AI workloads aligned with frameworks such as MITRE ATLAS, recommending enhancements to enable effective monitoring and response from the SOC across the entire AI attack surface.

• Review identity, access, and secrets management for models, tools, and data, advising on improvements for least-privilege access.

• Assist in compliance within a regulated environment by providing audit-ready assessments, evidence, and documentation.

• Foster innovation within the team — Explore and, where feasible, implement Agentic AI usage within the unit to optimize time-consuming tasks (e.g., chatbots, automation with Hermes or n8n, etc).

⛳️ Requirements

• Possess valid and relevant certifications or equivalent, verifiable experience in Cyber Security and/or Information Technology.

• Bring robust experience in infrastructure and security engineering, including Linux, networking, cloud, IAM, container security, and automation.

• Be familiar with both self-hosted LLM deployments and cloud LLM platforms (e.g., Azure Foundry, Amazon Bedrock, Google VertexAI, Ollama, LMStudio, etc.).

• Capable of reviewing and assessing AI systems against best practices and providing clear advice to teams on areas to harden, improve, or remediate continuously.

• Have previous knowledge of LLM-specific threats, including prompt injection, sensitive data disclosure, data/model poisoning, excessive agency, insecure output handling, and supply chain risks, along with strategies for mitigation.

• Be knowledgeable about various AI security frameworks and guidelines, including the OWASP Top 10 for LLM Applications (2025) and Agentic Applications (2026), MITRE ATLAS, NIST AI RMF, ISO/IEC 42001, CISA/NSA guidance, and the EU AI Act, as well as how to translate them into actionable controls.

• Have prior experience in the design evaluation and implementation of guardrails, including prompt-injection defenses, output validation, and hallucination mitigation.

• Have exposure to infrastructure-as-code tools (Terraform, Ansible) and CI/CD pipelines to establish repeatable controls.

• Experience working in regulated environments such as gaming, finance, or healthcare.

• Exhibit strong communication, presentation, and collaboration skills — excellent documentation abilities and cross-team collaboration are essential for this role.

🏝️ Benefits

• Competitive salary

• Flexible working arrangements

• Professional development opportunities