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- Tasks: Lead the design and implementation of security frameworks for AI/ML systems.
- Company: Join a forward-thinking company focused on AI security in London.
- Benefits: Enjoy hybrid work options and competitive pay.
- Why this job: Be at the forefront of AI security, shaping safe and compliant systems.
- Qualifications: Experience in AI/ML security and proficiency in programming languages required.
- Other info: Consulting background is a plus; rights to work in the UK are essential.
The predicted salary is between 43200 - 72000 £ per year.
We are seeking an experienced AI Security Architect to lead the design, development, and implementation of robust security frameworks across our AI and machine learning environments. This is a strategic role focused on securing the full lifecycle of AI/ML systems—from model development and training data to deployment and ongoing operations.
You will work cross-functionally with data scientists, engineers, and business stakeholders to ensure that our AI systems are safe, resilient, compliant, and aligned with emerging regulatory frameworks such as the EU AI Act, NIST AI RMF, GDPR, and more.
Key skills:- Proven experience as a Security Architect with a strong focus on AI/ML security.
- Deep understanding of AI/ML systems, algorithms, models, and common frameworks.
- Solid background in secure software development and architecture, particularly within data-heavy or AI environments.
- Proficiency in Python, R, C/C++, or Java, and awareness of security risks associated with these languages.
- Familiarity with key ML frameworks such as TensorFlow, PyTorch, JAX, and scikit-learn.
- Strong grasp of DevOps/CI/CD workflows and secure SDLC methodologies.
- Experience securing cloud-native environments, including containerized services (e.g., Kubernetes) and CI/CD orchestration tools.
- Knowledge of AI-specific threat vectors like adversarial attacks, data poisoning, and prompt injection, and familiarity with the MITRE ATLAS framework.
- Proficiency in threat modeling and security assessment techniques for AI/ML systems.
- Understanding of relevant laws and standards (EU AI Act, DSA, DMA, GDPR, ISO 27001, etc.) and their security implications.
- Demonstrated ability to design and implement access controls, identity management, and encryption for AI/ML environments.
- Consulting background is a plus.
- Strong communication skills (oral & written).
- Rights to work in the UK is a must (No Sponsorship available).
- Develop and implement enterprise-wide security strategies, policies, and frameworks for AI/ML systems.
- Design secure architectures for AI/ML platforms, CI/CD pipelines, and data workflows.
- Participate in organizational architecture discussions to support the secure development and operation of AI/ML workloads.
- Lead security risk assessments and threat modeling for AI/ML applications—identifying vulnerabilities and recommending mitigation strategies.
- Contribute to testing and validation of AI models and LLMs with a focus on trust, safety, fairness, bias, and adversarial robustness.
- Integrate security best practices into AI/ML pipelines, algorithms, and applications.
- Establish strong access controls, authentication, and encryption protocols to protect sensitive AI assets and data.
AI Security Architect employer: Focus on SAP
Contact Detail:
Focus on SAP Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Security Architect
✨Tip Number 1
Familiarise yourself with the latest AI security frameworks and regulations, such as the EU AI Act and NIST AI RMF. This knowledge will not only help you understand the role better but also demonstrate your commitment to staying updated in this rapidly evolving field.
✨Tip Number 2
Network with professionals in the AI and cybersecurity sectors. Attend relevant meetups, webinars, or conferences to connect with others in the field. This can lead to valuable insights and potential referrals that could enhance your chances of landing the job.
✨Tip Number 3
Showcase your hands-on experience with AI/ML frameworks like TensorFlow and PyTorch. If you have personal projects or contributions to open-source initiatives, be ready to discuss them. Practical experience can set you apart from other candidates.
✨Tip Number 4
Prepare for technical discussions by brushing up on threat modelling and security assessment techniques specific to AI/ML systems. Being able to articulate your approach to identifying vulnerabilities and recommending mitigation strategies will impress interviewers.
We think you need these skills to ace AI Security Architect
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience as a Security Architect, particularly in AI/ML security. Emphasise relevant projects and skills that align with the job description, such as your proficiency in Python, R, or Java, and your understanding of AI-specific threat vectors.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI security and your strategic approach to securing AI/ML systems. Mention specific frameworks and regulations you are familiar with, like the EU AI Act and GDPR, to demonstrate your knowledge and relevance to the role.
Highlight Cross-Functional Collaboration: In your application, mention any experience working cross-functionally with data scientists, engineers, and business stakeholders. This shows your ability to communicate effectively and collaborate on securing AI systems, which is crucial for this role.
Showcase Your Problem-Solving Skills: Provide examples of how you've identified vulnerabilities and implemented mitigation strategies in previous roles. This could include details about security risk assessments or threat modelling you've conducted, which are key responsibilities for the position.
How to prepare for a job interview at Focus on SAP
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with AI/ML security in detail. Highlight specific projects where you designed secure architectures or implemented security frameworks, and be ready to explain the technologies and methodologies you used.
✨Understand Regulatory Frameworks
Familiarise yourself with relevant laws and standards such as the EU AI Act and GDPR. Be ready to discuss how these regulations impact AI security and how you've ensured compliance in past roles.
✨Demonstrate Cross-Functional Collaboration
Since this role involves working with data scientists and engineers, prepare examples of how you've successfully collaborated with different teams. Emphasise your communication skills and ability to bridge technical and non-technical discussions.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills in real-world situations. Think about potential threats to AI systems and how you would address them, including threat modelling and risk assessment techniques.
