AI Security Architect

NTT Ltd.
Epworth, UK
about 1 month ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Microsoft Azure Cloud Computing Cloud Computing Security Cyber Security Continuous Integration Information Leak Prevention Data Security DevOps Identity and Access Management
+17 more
Information Systems Security Architecture Professional Key Management Network Security Machine Learning Tensorflow Secure Coding Google Cloud Data Ingestion Pytorch Large Language Models Software Security AI Platforms Kubernetes Information Technology Machine Learning Operations Software Version Control Devsecops

Job description

We are seeking an experienced AI Security Architect to design, implement, and govern secure AI/ML systems across the enterprise. This role is responsible for embedding security, privacy, and trust into AI solutionsfrom model development and deployment to monitoring and lifecycle management. The ideal candidate will combine deep cybersecurity expertise with hands-on knowledge of AI/ML technologies, ensuring that AI systems are resilient against adversarial threats, data leakage, and misuse.

What youll be doing:

  1. AI Security Strategy & Architecture
  • Define and lead the AI security architecture roadmap aligned to enterprise security strategy.
  • Develop secure-by-design frameworks for AI/ML pipelines, including data ingestion, training, inference, and deployment.
  • Establish AI trust, risk, and compliance controls (e.g., explainability, fairness, robustness).
  1. Threat Modelling & Risk Management
  • Conduct threat modelling for AI systems, identifying vulnerabilities such as:
  • Adversarial attacks (evasion, poisoning)
  • Model inversion and extraction
  • Data leakage and privacy risks
  • Define and implement risk mitigation strategies and controls.
  • Perform AI security risk assessments and integrate findings into governance processes.
  1. Secure AI/ML Lifecycle
  • Integrate security into ML pipelines (MLSecOps) including CI/CD and MLOps frameworks.
  • Define controls for:
  • Secure dataset handling and lineage
  • Model versioning and integrity validation
  • Access control and secrets management
  • Embed automated security testing into model development pipelines.
  1. Data Protection & Privacy
  • Ensure compliance with data protection regulations (e.g., GDPR, HIPAA where applicable).
  • Implement privacy-preserving techniques such as:
  • Differential privacy
  • Federated learning
  • Data anonymization and synthetic data
  • Define policies for sensitive data usage in AI models.
  1. Security Controls for Emerging AI Risks
  • Design safeguards for:
  • Large Language Models (LLMs) and generative AI (prompt injection, hallucinations, data exfiltration)
  • API and model endpoint security
  • Implement guardrails and monitoring solutions for generative AI usage.
  1. Governance, Compliance & Standards
  • Establish AI security standards, policies, and guidelines aligned to frameworks such as:
  • NIST AI Risk Management Framework
  • ISO/IEC 27001, 23894
  • Support regulatory compliance and audits related to AI security.
  1. Collaboration & Advisory
  • Partner with data scientists, ML engineers, DevOps, and security teams to embed security practices.
  • Act as a trusted advisor to business and technology stakeholders on AI-related risks.
  • Provide security design reviews for AI initiatives.
  1. Monitoring & Incident Response
  • Define monitoring for model drift, anomalies, and misuse detection.
  • Develop playbooks for AI-related security incidents, including model compromise or data breaches.
  • Lead investigations involving AI system risks.

Requirements

  • 20+ years of experience in cybersecurity, with at least 3+ years in AI/MLsecurity or data security.
  • Proven experience designing secure architectures for AI/ML systems.
  • Strong knowledge of:
  • Machine learning frameworks (TensorFlow, PyTorch, etc.)
  • Cloud platforms (Azure, AWS, GCP) and AI services
  • Identity & access management, encryption, and network security
  • Experience in threat modeling and risk assessment methodologies.
  • Bachelors or Masters degree in Computer Science, Cybersecurity, AI/ML, or related field.

Preferred Qualifications

  • Certifications such as:
  • CISSP, CISM, CCSP
  • Certified AI Security (e.g., CAISP or similar)
  • Experience with:
  • MLOps platforms (e.g., MLflow, Kubeflow)
  • AI red teaming and adversarial testing
  • Knowledge of secure coding and DevSecOps practices.
  • Familiarity with Responsible AI principles and ethical AI frameworks.

Key Skills

  • AI/ML security and adversarial techniques
  • Cloud security architecture
  • Data privacy and protection
  • Threat modeling and risk analysis
  • DevSecOps / MLSecOps
  • API and application security
  • Governance, risk, and compliance (GRC)
  • Strong communication and stakeholder management

About the company

At NTT DATA, you have endless opportunities to think big, act bold and take ownership. As a $30+ billion business and technology services, AI and digital infrastructure leader, we co-innovate solutions with clients and partners globally for business and societal impact. Serving 75% of the Fortune Global 100, with experts in over 70 countries, we encourage experimentation and recognize great work. Proudly a Global Top Employer, NTT DATA is part of NTT Group, which invests over $3 billion annually in R Make this the place where you belong, learn, and build your network. Make this the place whereyougrow.

what well offer you: We offer a range of tailored benefits that support your physical, emotional, and financial wellbeing. Our Learning and Development team ensure that there are continuous growth and development opportunities for our people. We also offer the opportunity to have flexible work options.

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