AI Security Engineer (Cybersecurity)

TL;DR

AI Security Engineer (Cybersecurity): Securing the design, construction, and operation of AI systems across on-premise and cloud environments with an accent on infrastructure security and agentic workloads. Focus on hardening LLM deployments, implementing guardrails, and ensuring compliance with AI security frameworks.

Location: 37 Kilkis, Latsia, Nicosia, Cyprus

Company

Leading technology company in the gaming industry providing B2B software, services, and platform technology.

What you will do

• Review AI systems and infrastructure, including LLM deployments and vector stores, to provide hardening recommendations.
• Assess and strengthen AI guardrails such as prompt-injection defenses, rate limiting, and authentication.
• Advise on secure-by-design AI architecture using frameworks like OWASP, MITRE ATLAS, and NIST AI RMF.
• Evaluate the AI supply chain, including model provenance and AIBOM/SBOM scanning.
• Define security standards and reference patterns for the secure operation of AI across the business.
• Enhance logging and observability for AI workloads to improve SOC monitoring and response.

Requirements

• Valid certifications or verifiable experience in Cyber Security or Information Technology.
• Solid experience in infrastructure and security engineering, including Linux, networking, cloud, IAM, and container security.
• Hands-on experience with both self-hosted (Ollama, LMStudio) and cloud LLM platforms (Azure Foundry, Amazon Bedrock, Google VertexAI).
• Deep knowledge of LLM-specific threats such as prompt injection, data poisoning, and excessive agency.
• Familiarity with AI security guidelines including OWASP Top 10 for LLM/Agentic apps, EU AI Act, and NIST AI RMF.
• Experience with Infrastructure-as-Code (Terraform, Ansible) and CI/CD pipelines.

Nice to have

• Experience building CI/CD security gates and guardrails.
• Proficiency in Python and Bash scripting.
• Hands-on experience securing MCP/agentic AI infrastructure.
• Familiarity with AIBOM/SBOM tooling (e.g., OWASP Dependency-Track) and MLSecOps practices.
• Experience with AI red-teaming.

Culture & Benefits

• Collaborative environment working across System Security, Application Security, and the AI Committee.
• Culture of ownership, curiosity, and a proactive approach to complex security challenges.
• Opportunity for continuous learning in the rapidly evolving field of AI security.
• Direct impact on the company's AI adoption strategy and future security posture.
• Inclusive workplace committed to diversity and equal opportunities.