At a Glance
- Tasks: Lead the design and implementation of security frameworks for AI/ML systems.
- Company: Join a forward-thinking company focused on AI security and compliance.
- Benefits: Enjoy hybrid work options and a dynamic team environment.
- Why this job: Be at the forefront of AI security, shaping safe and compliant technologies.
- Qualifications: Proven experience in AI/ML security and strong programming skills 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).
Responsibilities:
- 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.
Should you be interested in being considered for this position and would like to discuss further, please apply with your latest CV or share your CV directly with me at christophe.ramen@focusonsap.org.
AI Security Architect employer: Focus on SAP
Contact Detail:
Focus on SAP Recruiting Team
christophe.ramen@focusonsap.org
StudySmarter Expert Advice 🤫
We think this is how you could land AI Security Architect
✨Tip Number 1
Network with professionals in the AI and security fields. Attend industry conferences, webinars, or local meetups to connect with others who work in AI security. This can help you gain insights into the role and potentially get referrals.
✨Tip Number 2
Stay updated on the latest trends and regulations in AI security. Familiarise yourself with frameworks like the EU AI Act and NIST AI RMF, as well as emerging threats. This knowledge will not only prepare you for interviews but also demonstrate your commitment to the field.
✨Tip Number 3
Showcase your hands-on experience with relevant tools and technologies. If you've worked with ML frameworks like TensorFlow or PyTorch, be ready to discuss specific projects where you implemented security measures. Practical examples can set you apart from other candidates.
✨Tip Number 4
Prepare for technical interviews by brushing up on your coding skills in Python, R, C/C++, or Java. Be ready to solve problems related to AI security and discuss how you would approach securing AI/ML systems in a real-world scenario.
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 technologies you've worked with, such as Python, TensorFlow, or Kubernetes.
Craft a Strong Cover Letter: Write a cover letter that specifically addresses the key skills mentioned in the job description. Discuss your understanding of AI/ML systems and how your background aligns with the responsibilities outlined for the role.
Showcase Relevant Experience: In your application, provide examples of past work where you developed security frameworks or conducted threat assessments for AI/ML systems. Use metrics to demonstrate the impact of your contributions.
Highlight Communication Skills: Since strong communication skills are essential for this role, include instances where you've effectively communicated complex security concepts to non-technical stakeholders or collaborated cross-functionally.
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 questions that assess your problem-solving skills in real-world scenarios. Think about potential threats to AI systems, such as adversarial attacks or data poisoning, and how you would mitigate these risks.