Senior AI Security Engineer (R-19324)
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- open for 54 days (30+ days starts to look stale)
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- no salary disclosed (correlates with ghost postings)
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About the role
What’s on Offer at D&B Ireland
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)
At Dun & Bradstreet, we are 6,000 friendly colleagues around the world waiting to meet you and give you the opportunity to grow your career.
Responsibilities:
Design and implement enterprise-grade security architectures for AI, GenAI, and ML platforms, pipelines, and products (not just lead/define)
Build and maintain automated security controls for LLM-based systems, agentic AI frameworks, and AI-driven APIs at scale
Develop and operationalize CI/CD pipeline security , embedding automated security testing, validation, SAST/SCA, and monitoring into deployment workflows
Lead threat modeling, red-teaming, and adversarial testing initiatives targeting AI systems, models, and data ecosystems
Code and deploy security solutions to mitigate AI-specific risks: prompt injection, data leakage, model exfiltration, model poisoning, misuse detection
Build secure AI data pipelines , implementing data governance, lineage protection, and privacy-preserving mechanisms end-to-end
Define and implement secure identity, authentication, authorization, and trust models for human-to-AI and agent-to-agent interactions
Develop infrastructure-as-code (IaC) security controls and secure-by-default cloud environments on Google Cloud Platform (GCP)
Develop automation tools and scripts to reduce manual security toil and scale security operations
Collaborate with platform, cloud, and infrastructure teams to integrate security into infrastructure provisioning and orchestration
Influence enterprise security policies, governance frameworks, and regulatory compliance initiatives related to AI
Mentor engineers; provide technical leadership and hands-on guidance across programs
Stay at the forefront of emerging AI threats and translate insights into code, automation, and architectural improvements
Essential skills and/or Certifications:
Bachelor's degree in Computer Science, Artificial Intelligence, Cybersecurity, or related field
8–12 years of relevant experience , including:
5+ years hands-on security engineering with demonstrated contributions to production systems
Technical Expertise:
Strong programming proficiency in Python, Go, or Java — able to design, build, and maintain production security tools and integrations
Expert-level DevSecOps skills : CI/CD pipeline security (GitHub Actions, GitLab CI, Jenkins), IaC scanning (Terraform, CloudFormation), SAST/SCA tools (Snyk, SonarQube, Checkmarx)
Cloud security hands-on : Google Cloud Platform (GCP) including IAM policies, VPCs, Cloud KMS, secrets management, and GCP-native security services
API security : Designing and securing API gateways, rate limiting, authentication mechanisms, and API threat models
Distributed systems security : Microservices, service mesh (Istio, Linkerd), inter-service communication security
Infrastructure security : Network segmentation, encryption (in-transit and at-rest), audit logging, secrets management (HashiCorp Vault, cloud vaults)
Scripting & automation : Bash, Python for building monitoring, compliance, and remediation automation
Desirable:
Experience with AI/ML platform security (LLMs, RAG architectures, vector databases, agentic frameworks)
AI/ML security knowledge: threat models for LLMs, adversarial techniques (prompt injection, model poisoning), secure model serving architectures
Experience with security compliance automation (CIS Benchmarks, NIST frameworks)
Hands-on red-teaming or adversarial testing of AI systems
Open-source contributions to security or DevSecOps tools
Cloud security certifications (GCP Professional Cloud Security Engineer, GCP Associate Cloud Security Engineer)
Experience with secure MLOps/ML lifecycle security
Soft Skills:
Ownership mindset; solve problems proactively, be curious, take action
Strong cross-functional collaboration in global, multi-stakeholder environments
Excellent communication — translate complex security concepts for technical and non-technical audiences
Mentorship and technical leadership capability
Continuous growth mindset; commitment to staying current with AI security landscape
Fluency in English; local language fluency a plus
Proficiency in Microsoft Office Suite
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