Deloitte Cyber team is looking to deliver powerful solutions to help clients navigate the ever-changing threat landscape, specifically in securing Artificial Intelligence and Machine Learning solutions on the Microsoft Azure platform.
Requirements
- 4+ years of experience in technical consulting, client problem solving, architecting and designing solutions in a consulting role with project leadership and/or architect experience in Azure; with a security focus strongly preferred
- Familiarity with Microsoft Copilot, GitHub Copilot, Azure AI Services, including practical experience with Azure Machine Learning and Azure OpenAI
- Proven experience with AI/ML model evaluation, adversarial testing, and a deep understanding of machine learning algorithms and data processing techniques, particularly in the context of security vulnerabilities
- Expertise in designing, implementing, and securing MLOps pipelines, encompassing model registry security, secure model deployment, and runtime security monitoring for AI models
- Experience with AI Security Posture Management (AI-SPM) tools, such as Microsoft Defender for Cloud (including its AI-SPM modules) or third-party solutions like Wiz, for continuous monitoring and compliance of AI assets
- Intermediate programming skills in Python, Java, or other relevant languages, with a focus on developing secure and scalable AI solutions
- Comprehensive understanding of cryptographic principles and their practical application in securing AI models, data at rest and in transit, and communication channels within AI systems
Responsibilities
- Leading the security implementation for various Azure AI Services, including Azure OpenAI Service, Azure Machine Learning, Azure Cognitive Services, and Azure AI Studio, ensuring protection from development to deployment
- Architecting, designing, and implementing comprehensive security playbooks for AI models, focusing on encryption, access control, data integrity, model scanning, and overall AI model governance
- Developing and enforcing security controls for Microsoft Copilot and GitHub Copilot usage, encompassing data governance, content filtering, access management, code scanning, vulnerability detection, and intellectual property protection
- Designing and building secure Continuous Integration/Continuous Delivery (CI/CD) pipelines specifically tailored for the training, tuning, and deployment of Machine Learning and Generative AI models, ensuring security is embedded throughout the MLOps lifecycle
- Establishing and maintaining secure development environments within Azure AI Studio and Azure Machine Learning Studio, with seamless integration of GitHub Copilot and Microsoft Copilot environments
- Implementing robust controls for model registries and AI model repositories to scan for and mitigate vulnerabilities, ensuring the integrity and security of all stored models
- Securing the underlying Azure platform by implementing appropriate cyber security controls to protect sensitive data stores and large language model (LLM) services
Other
- BA/BS Degree preferred. Ideally in Computer Science, Cyber Security, Information Security, Engineering, Information Technology
- Certifications such as: Microsoft roles-based certifications (e.g., Azure AI Engineer Associate, Azure Security Engineer Associate), CCSP, CCSK, CISSP certification a plus
- Leading cross-functional teams in the successful delivery of secure AI projects, ensuring alignment with business goals, regulatory requirements, and industry best practices
- Engaging with stakeholders, including data scientists, AI engineers, business stakeholders, and compliance teams, to ensure comprehensive security coverage and foster a security-first mindset
- Developing and executing strategic roadmaps for AI security initiatives, staying ahead of emerging threats, and adapting to evolving regulatory changes
