Azure AI Security Senior Consultant

Position Summary

Our Deloitte Cyber team understands the unique challenges and opportunities businesses face in cybersecurity. Join our team to deliver powerful solutions to help our clients navigate the ever-changing threat landscape. Through powerful solutions and managed services that simplify complexity, we enable our clients to operate with resilience, grow with confidence, and proactively manage to secure success.

Recruiting for this role ends 12/31/2025

Work you'll do:

As a Senior Consultant, you will be at the forefront with our clients, supporting them with their AI security needs, specifically helping them navigate the complexities of securing Artificial Intelligence and Machine Learning solutions on the Microsoft Azure platform. This will include:

• 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
• Automating security guardrails through the development and deployment of Azure Policies, ARM templates, Bicep templates, and Terraform modules, ensuring consistent application of security controls across Azure AI services
• Managing data security by implementing encryption, tokenization, anonymization, and access control for various Azure data stores, including Azure Storage, Azure SQL Database, Azure Cosmos DB, and Azure Data Lake
• Deploying and configuring AI Firewall solutions, such as Azure AI Content Safety and security proxies, to effectively detect and prevent sophisticated attacks like prompt injection, jailbreaking attempts, and data leakage
• Leading the secure deployment of Azure Machine Learning models on various Azure compute services, including Azure Kubernetes Service (AKS), Azure Container Instances (ACI), and serverless endpoints, ensuring secure and scalable AI deployments
• Conducting rigorous testing and validation, including adversarial testing, bias detection, model monitoring, and red team exercises, for Azure AI services and Copilot implementations to identify and remediate security weaknesses
• Deploying runtime scanners and monitoring solutions to detect vulnerabilities and anomalies in deployed AI models, enabling proactive threat detection and response
• Deploying and managing AI Security Posture Management (AI-SPM), Cloud Security Posture Management (CSPM), and Data Security Posture Management (DSPM) modules within Microsoft Defender for Cloud or leveraging third-party tools for comprehensive security posture management
• Ensuring continuous compliance through the utilization of Azure Policy, Microsoft Purview, and Azure Defender capabilities for automated auditing, compliance monitoring, and the generation of detailed reporting dashboards
• Implementing Responsible AI Controls, focusing on fairness, reliability, safety, privacy, inclusiveness, transparency, and accountability measures across all AI solutions, promoting ethical and secure AI development
• Configuring advanced content safety filters for harmful content detection within generative AI applications, safeguarding against misuse and malicious content generation
• 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
• Collaborating with Data Engineers and Architects to secure the entire Azure Data Pipeline, from data ingestion to processing and storage, ensuring end-to-end data security for AI workloads.
• Mentoring and guiding team members in AI security best practices and emerging technologies, fostering a culture of continuous learning and expertise development
• Contribute to Point-of-Views (PoVs) on providing leading practices to our clients on the Azure AI security challenges they face

• 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
• Familiarity with and practical application of industry-standard security frameworks and best practices, including OWASP, NIST, and MITRE ATLAS, tailored for AI and cloud environments

• 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