Senior AI Security Engineer (R-19324)

Dnb; Dublin; On-site; EUR 140,000 - 190,000; Full time

Benefits offered by this job

25 days annual leave

Holiday buy & sell (up to 5 days)

Flexible working - hybrid model

Employee Health Insurance

Mental Health Support program

Pension Contribution

Family Friendly Leave

Life Assurance

Educational Assistance Program

Life-Style Account (D&B match up to €-

Job summary

Dun & Bradstreet seeks a Senior AI Security Engineer to define and advance enterprise security strategies for AI/GenAI platforms. You will lead secure AI system designs, drive security-by-design practices, and partner with engineering and risk leadership to address AI threats at scale.

The role requires deep expertise in AI/ML security, cloud security, and secure SDLC, with a track record of securing large distributed systems. Hybrid work and comprehensive benefits are provided.

Qualifications

• 8–12 years of relevant experience in security engineering with AI/ML platforms.
• Deep understanding of application and cloud security, threat modeling, and risk mitigation.
• Proven experience designing and securing large-scale distributed systems, microservices, and API ecosystems.

Responsibilities

• Lead the design, development, and evolution of enterprise-grade security architectures for AI, GenAI, and ML platforms, pipelines, and products.
• Define and drive security strategy, standards, and reference architectures for AI systems across the organization.
• Serve as a technical authority in AI security, advising engineering and leadership on secure design, threat mitigation, and risk acceptance decisions.
• Implement advanced security controls for LLM-based systems, agentic AI frameworks, and AI-driven APIs at scale.
• Lead complex threat modeling, red-teaming, and adversarial testing initiatives targeting AI systems, models, and data ecosystems.
• Establish and operationalize controls to mitigate AI-specific risks including prompt injection, data leakage, model exfiltration, model poisoning, and misuse scenarios.
• Drive security integration across the AI lifecycle, including model development, training, evaluation, deployment, and runtime operations.
• Define and implement secure identity, authentication, authorization, and trust models for human-to-AI and agent-to-agent interactions.
• Lead the design of secure AI data architectures, including data governance, lineage protection, and privacy-preserving mechanisms.
• Champion DevSecOps practices for AI platforms, embedding automated security testing, validation, and monitoring into CI/CD pipelines.
• Collaborate with platform, cloud, and infrastructure teams to ensure secure-by-default environments across multi-cloud ecosystems.
• Influence enterprise security policies, governance frameworks, and regulatory compliance initiatives related to AI.
• Lead incident response and forensic analysis for AI-related security events and vulnerabilities.
• Mentor and coach engineers; provide technical leadership across programs and communities of practice.
• Drive cross-functional security initiatives, aligning stakeholders across engineering, product, legal, and risk domains.
• Stay at the forefront of emerging AI threats, technologies, and industry best practices, translating insights into actionable improvements.

Skills

Leadership

Communication

Problem solving

Collaboration

English language

Education

Bachelor’s degree in Computer Science, AI, Cybersecurity or related field

Job description

Senior AI Security Engineer

The Senior AI Security Engineer is responsible for defining, designing, and advancing enterprise-wide security strategies and architectures for AI, GenAI, and machine learning platforms.

This role leads the development of secure AI systems at scale by embedding advanced security principles across the AI lifecycle and driving the adoption of standardized, security-by-design practices. The Senior AI Security Engineer partners with engineering, platform, and risk leadership to proactively address emerging AI threats, strengthen organizational security posture, and ensure resilient, compliant, and scalable AI deployments. This role operates with significant autonomy and influences security direction across multiple teams and domains.

Benefits

• 25 days annual leave (plus 2 paid volunteer days & 1 paid un-sick day)
• Holiday buy & sell (the option to buy or sell up to 5 additional days per year)
• Flexible working - hybrid model
• Employee Health Insurance
• Mental Health Support program
• Pension Contribution
• Family Friendly Leave (Maternity, Paternity, Parental, Marriage and Bereavement)
• Life Assurance
• Educational Assistance Program
• Life-Style Account (D&B will match your contributions up to €40 per month and can be used to claim for a range of health-related, leisure or lifestyle activities)

Responsibilities

• Lead the design, development, and evolution of enterprise-grade security architectures for AI, GenAI, and ML platforms, pipelines, and products
• Define and drive security strategy, standards, and reference architectures for AI systems across the organization
• Serve as a technical authority in AI security, advising engineering and leadership teams on secure design, threat mitigation, and risk acceptance decisions
• Implement advanced security controls for LLM-based systems, agentic AI frameworks, and AI-driven APIs at scale
• Lead complex threat modeling, red-teaming, and adversarial testing initiatives targeting AI systems, models, and data ecosystems
• Establish and operationalize controls to mitigate AI‑specific risks including prompt injection, data leakage, model exfiltration, model poisoning, and misuse scenarios
• Drive security integration across the AI lifecycle, including model development, training, evaluation, deployment, and runtime operations
• Define and implement secure identity, authentication, authorization, and trust models for human-to‑AI and agent-to-agent interactions
• Lead the design of secure AI data architectures, including data governance, lineage protection, and privacy‑preserving mechanisms
• Champion DevSecOps practices for AI platforms, embedding automated security testing, validation, and monitoring into CI/CD pipelines
• Collaborate with platform, cloud, and infrastructure teams to ensure secure‑by‑default environments across multi‑cloud ecosystems
• Influence and contribute to enterprise security policies, governance frameworks, and regulatory compliance initiatives related to AI
• Lead incident response and forensic analysis for AI‑related security events and vulnerabilities
• Mentor and coach engineers; provide technical leadership across programs and communities of practice
• Drive cross‑functional security initiatives, aligning stakeholders across engineering, product, legal, and risk domains
• Stay at the forefront of emerging AI threats, technologies, and industry best practices, and translate insights into actionable improvements

Qualifications

• Bachelor’s degree in Computer Science, Artificial Intelligence, Cybersecurity or related field
• 8 - 12 years of relevant experience, including significant experience in security engineering and deep specialization in AI/ML platforms.
• Deep understanding of application and cloud security, threat modeling, and risk mitigation techniques.
• Proven experience designing and securing large‑scale distributed systems, microservices, and API ecosystems
• Advanced expertise in AI/ML security, including LLMs, RAG architectures, vector databases, and agentic frameworks
• Strong knowledge of AI threat models, adversarial AI techniques, and attack vectors (e.g., prompt injection, model manipulation, data poisoning)
• Hands‑on experience implementing security controls across data, model, API, and infrastructure layers
• Extensive experience with cloud security (AWS, Azure, GCP) including IAM, network security, and platform services
• Expertise in DevSecOps, automation, and secure SDLC integration
• Experience with containerization, Kubernetes security, and modern infrastructure protection practices
• Ability to define and influence enterprise security standards and architectural decisions
• Strong leadership, stakeholder management, and communication skills
• Experience working across multi‑stakeholder, global engineering environments
• Proficiency in Microsoft Office Suites Skills
• Show an ownership mindset in everything you do; be a problem solver, be curious and inspired to take action, be proactive, seek ways to collaborate and connect with people and teams in support of driving success.
• Continuous growth mindset, keep learning through social experiences and relationships with stakeholders, experts, colleagues and mentors as well as widen and broaden your competencies through structural courses and programs.
• Where applicable, fluency in English and languages relevant to the working market.

Dun & Bradstreet is an Equal Opportunity Employer.