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- Tasks: Secure AI models and workflows, implement security tools, and run threat modelling workshops.
- Company: Join DevSecAI, the world's first AI Security Enablement Company, leading in AI security solutions.
- Benefits: Enjoy a hybrid work model, global exposure, and opportunities for professional growth.
- Why this job: Be at the forefront of AI security, shaping how the world protects AI technologies.
- Qualifications: Skills in AI security engineering and experience with AI tools are essential.
- Other info: Work with a diverse team across various industries, from finance to healthcare.
The predicted salary is between 48000 - 72000 £ per year.
DevSecAI is the world's first AI Security Enablement Company. We embed expert AI security engineers within clients’ teams and provide a DevSecAI SaaS platform for tracking clients' AI security tasks. We support clients globally with over 27 DevSecAI engineers deployed in the UK, US, Canada, Switzerland, Malaysia and Singapore. We have built 6 AI Security labs that research and test the latest AI security tools before deploying to clients. We are expanding globally to become the world's leading AI Security company.
This is a full-time hybrid role for a DevSecAI Engineer located in the UK. The DevSecAI Engineer will be responsible for securing AI models, LLMs, GenAI workflows, and data pipelines using vendor-agnostic tools. They will work closely with other AI Embedded Engineers to ensure the security of AI systems throughout the AI Development Lifecycle across Finance, Government, Utilities, Health and more. You’ll be part of a new kind of security - embedded into client AI products, tracking their AI security maturity, implementing AI security tools within their workflows, running threat modelling workshops, red teaming against ML Models, hardening ML APIs, and helping define how the world secures artificial intelligence.
What You’ll Do:
- Embed within client organisations to implement AI Security Tooling
- Perform threat modelling for GenAI & LLM-enabled apps
- Test and secure AI/ML pipelines, APIs, dashboards, and cloud infrastructure
- Help design secure-by-default AI workflows (from data ingestion to deployment)
- Work across tools like Amazon SageMaker, Azure OpenAI, AWS Bedrock, Hugging Face, etc.
- Stay ahead of AI privacy, compliance and attack trends
- Contribute to client work, internal R&D, or platform development - or all three
Qualifications:
- AI Security Engineering, AI Model Security, and Data Pipeline Security skills
- Experience with various AI security tools and technologies
- Knowledge of AI lifecycle management and GenAI workflows
- Strong problem-solving and analytical skills
- Excellent written and verbal communication skills
- Ability to collaborate with cross-functional teams
Certifications:
- AWS AI practitioner
- Microsoft Certified Azure AI Fundamentals
- Terraform Associate
- Cyber Agoge DevSecAI Certificate
- Cyber Agoge DevSecOps Certificate
- Microsoft AI and ML Engineering Professional Certificate
DevSecAI Engineer employer: DevSecAI
Contact Detail:
DevSecAI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land DevSecAI Engineer
✨Tip Number 1
Familiarise yourself with the latest AI security tools and technologies mentioned in the job description, such as Amazon SageMaker and Azure OpenAI. This knowledge will not only help you during interviews but also demonstrate your proactive approach to understanding the role.
✨Tip Number 2
Engage with online communities or forums focused on AI security. Networking with professionals in this field can provide insights into current trends and challenges, which you can discuss during your interview to show your enthusiasm and commitment.
✨Tip Number 3
Consider running your own small projects or simulations that involve securing AI models or data pipelines. This hands-on experience will not only enhance your skills but also give you concrete examples to share when discussing your qualifications.
✨Tip Number 4
Stay updated on AI privacy and compliance regulations, as these are crucial for the role. Being knowledgeable about these topics will allow you to speak confidently about how you can contribute to the company's mission of securing AI systems.
We think you need these skills to ace DevSecAI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI security engineering, data pipeline security, and familiarity with tools like Amazon SageMaker and Azure OpenAI. Use keywords from the job description to align your skills with what DevSecAI is looking for.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI security and how your background makes you a perfect fit for the role. Mention specific projects or experiences that demonstrate your problem-solving skills and ability to work with cross-functional teams.
Showcase Relevant Certifications: List any relevant certifications such as AWS AI Practitioner or Microsoft Certified Azure AI Fundamentals prominently in your application. This will help demonstrate your commitment to the field and your technical expertise.
Prepare for Technical Questions: Anticipate technical questions related to AI security, threat modelling, and securing ML pipelines. Be ready to discuss your approach to implementing security tools and your understanding of compliance and privacy trends in AI.
How to prepare for a job interview at DevSecAI
✨Showcase Your Technical Skills
Make sure to highlight your experience with AI security tools and technologies during the interview. Be prepared to discuss specific projects where you've implemented security measures in AI models or data pipelines, as this will demonstrate your hands-on expertise.
✨Understand the AI Development Lifecycle
Familiarise yourself with the AI development lifecycle and be ready to explain how you can secure each phase. This knowledge will show that you understand the complexities of AI systems and can effectively contribute to their security.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills. Think about potential security threats in AI workflows and how you would address them. This will help you demonstrate your analytical thinking and ability to collaborate with cross-functional teams.
✨Communicate Clearly and Confidently
Since excellent communication skills are crucial for this role, practice articulating your thoughts clearly. Be concise and confident when discussing your experiences and ideas, as this will leave a positive impression on the interviewers.
