A rapidly expanding company at the forefront of the digital assets movement is hiring an AI Security Engineer for Dubai to secure AI-driven systems, including LLM-based applications, machine learning models, and AI-enabled automation tools. You will identify, assess, and mitigate security risks across the full AI lifecycle, from model development and training to deployment and runtime monitoring.
About the Role — Securing the AI Frontier
Core Focus: Protecting LLM applications, ML models, and AI automation tools
Threat Landscape: Prompt injection, model poisoning, data leakage, and adversarial attacks
Industry Position: Operating at the cutting edge of the digital assets and fintech movement
Team Culture: Work alongside one of the most brilliant teams in the industry
Growth Path: Career advancement within a dynamic, rapidly expanding company
Career Impact & AI Security Opportunity
Strategic Location: Dubai — a fast-growing hub for fintech and digital assets innovation
Technical Scope: Secure LLM integrations, RAG pipelines, and AI APIs across production systems
Governance Focus: Shape AI risk classification frameworks and internal security policy
Career Advancement: Direct influence over emerging AI security standards within a growing team
Position Overview
This AI Security Engineer role involves designing and implementing security controls for AI/ML systems across development, training, and production, securing LLM integrations and RAG pipelines, and conducting threat modeling for AI systems and data pipelines. You will identify and mitigate AI-specific threats such as prompt injection and model poisoning, integrate AI security checks into CI/CD pipelines, and ensure compliance with GDPR and financial industry regulations across all AI initiatives in Dubai.
Why This Role Matters: As AI Security Engineer at a fast-growing digital assets company, you protect LLM, RAG, and ML systems from emerging threats like prompt injection and adversarial attacks, build secure-by-design patterns for AI-powered features, integrate security checks directly into CI/CD pipelines, contribute to AI governance frameworks aligned with EU AI Act and NIST AI RMF standards, and position yourself at the cutting edge of one of tech’s fastest-growing security disciplines.
Key Responsibilities
AI/ML Security Architecture
- Design and implement security controls for AI/ML systems across development, training, and production
- Secure LLM integrations, RAG pipelines, and AI APIs
- Conduct threat modeling for AI systems and data pipelines
- Define secure-by-design patterns for AI-powered features
AI Threat Detection & Mitigation
- Identify and mitigate AI-specific threats, including prompt injection, jailbreak techniques, and model poisoning
- Address training data leakage, insecure model serialization, and excessive AI agent permissions
- Develop guardrails, content filters, and output validation mechanisms
- Implement monitoring for anomalous AI behavior across production systems
Secure Development & DevSecOps
- Integrate AI security checks into CI/CD pipelines
- Perform security reviews of ML code and AI-related infrastructure
- Secure model registries and artifact storage
- Collaborate with engineers and platform teams to enforce security standards
Data Protection, Compliance & Governance
- Ensure AI systems comply with GDPR and financial industry regulatory requirements
- Implement controls for sensitive data used in training and inference
- Perform AI risk assessments aligned with internal risk methodology
- Contribute to AI security standards, risk classification, and control frameworks
Qualifications & Requirements
Experience Requirements
- 3–5+ years in software engineering, ML engineering, or application security
- Hands-on experience with AI/ML systems, including LLMs and NLP models
- Experience conducting threat modeling and risk assessments
Technical Skills
- Python proficiency for automation and scripting
- Experience working with Claude Code
- Strong understanding of cloud platforms — AWS, Azure, or GCP
- Experience with API security, Docker, and Kubernetes
- Knowledge of AI-specific security risks and mitigations
Preferred Skills (PLUS)
- Familiarity with RAG architectures, vector databases, and ML pipelines such as MLflow, Kubeflow, or SageMaker
- Experience in fintech or other regulated environments
- Knowledge of AI governance frameworks, including the EU AI Act, NIST AI RMF, or ISO/IEC 42001
- Experience with AI red teaming and a background in cybersecurity or application security (OWASP,
Secure SDLC)
Soft Skills
- Strong analytical and problem-solving skills
- Ability to translate technical risk into business impact for non-security teams
- Cross-functional collaboration with ML, data, and product teams
- Clear documentation and communication skills
About the Company in Dubai
Join a dynamic and rapidly expanding company at the forefront of the digital assets movement, based in Dubai, UAE. Offering competitive pay, work-life harmony, generous time off, comprehensive health and pension benefits, a workation policy with 30 extra remote-work days, and paid volunteer days, this company invests heavily in its people while pushing the boundaries of secure AI innovation.
Career Excellence: Be a key player securing the future of AI-powered digital finance.
Who Should Apply?
- Application Security Engineers: Expanding into AI and ML-specific security risks
- ML/AI Engineers: Interested in transitioning into AI security architecture
- Cybersecurity Professionals: Familiar with OWASP and Secure SDLC practices
- AI Red Teamers: Experienced testing LLMs against adversarial and prompt injection attacks
- Fintech Security Specialists: Seeking a role within the digital assets and crypto space
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