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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 a hybrid work environment.
- Benefits: Enjoy flexible working options and a dynamic team culture.
- Why this job: Make a real impact by securing cutting-edge AI technologies and ensuring compliance with regulations.
- Qualifications: Proven experience in AI/ML security, strong coding skills, and knowledge of relevant laws required.
- Other info: Consulting background is a plus; rights to work in the UK are essential.
The predicted salary is between 48000 - 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 potentially even referrals for the position.
✨Tip Number 3
Showcase your hands-on experience with AI/ML frameworks like TensorFlow or PyTorch. If you have personal projects or contributions to open-source initiatives, be ready to discuss these during interviews to highlight your practical skills.
✨Tip Number 4
Prepare to discuss specific security challenges related to AI systems, such as adversarial attacks or data poisoning. Being able to articulate your understanding of these threats and how to mitigate them will set you apart from other candidates.
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 your proficiency in relevant programming languages and frameworks mentioned in the job description.
Craft a Strong Cover Letter: Write a cover letter that specifically addresses the key skills and responsibilities outlined in the job description. Use examples from your past experiences to demonstrate how you meet these requirements.
Showcase Relevant Projects: If you have worked on projects related to AI/ML security, include them in your application. Detail your role, the challenges faced, and the outcomes achieved to illustrate your expertise.
Highlight Compliance Knowledge: Since the role involves understanding regulatory frameworks like the EU AI Act and GDPR, make sure to mention any relevant experience or knowledge you have regarding compliance and security implications in your application.
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 approach risk assessments and mitigation strategies.
