Senior Cloud Security Engineer

About The Company
BMO Financial Group is a leading North American financial institution committed to delivering exceptional banking and financial services to its clients. With a rich history spanning over a century, BMO is recognized for its innovative approach, customer-centric philosophy, and dedication to fostering economic growth. The company operates through various divisions including personal banking, commercial banking, wealth management, and investment banking, serving millions of customers across North America. BMO prides itself on its strong corporate values, commitment to diversity and inclusion, and its focus on leveraging technology to enhance customer experiences and operational efficiency.
About The Role
We are seeking an enthusiastic and passionate professional for a Senior Cloud, AI & Data Security Engineer role who wants to design and implement security solutions for systems and services across AWS, Azure, and AI/ML platforms. The ideal candidate will establish the highest standards that meet and exceed security governance solutions and practices, provide assurance to management and auditors, and ensure sustained protection by embedding controls in operational and DevOps (CI/CD) practices with a focus on automation. This role requires a high level of technical security expertise and a strong sense of responsibility for monitoring, detecting, protecting, and maintaining the security of data, AI/ML systems, cloud platforms, and networks. As a key member of our team, you will have the opportunity to influence BMO's cloud, AI, and data security strategies, ensuring they are resilient, compliant, and aligned with industry best practices.
Qualifications
The successful candidate will possess a university degree in Engineering, Computer Science, Information Technology, or a related field. A minimum of 7-10 years of experience in developing and implementing security architectures or engineering within cloud, data, and AI security domains is required. Relevant security certifications such as CISSP, CCSP, CCSK, or Cloud Security Specialty certifications (e.g., AWS Certified Security Specialty, Microsoft Certified: Azure Security Engineer Associate) are highly preferred. Emerging or specialized certifications in AI security (e.g., CDAI, CompTIA AI+) or data security (e.g., CDPSE, CIPP) are considered advantageous. Candidates should demonstrate extensive knowledge of cloud architecture, security automation, and compliance frameworks such as CSA CCM, ISO 27001, ISO 27017, and NIST CSF. Familiarity with AI/ML development frameworks like TensorFlow, PyTorch, SageMaker, and Azure ML, along with understanding of AI-specific security risks, is essential. Additionally, experience with data security tools, encryption standards, and data privacy regulations (e.g., GDPR, CCPA) will be beneficial.
Responsibilities
Cloud Security

• Assess, design, implement, automate, and document security solutions, controls, and processes for AWS and Microsoft Azure cloud platforms.
• Develop and maintain security patterns for cloud platforms and services, ensuring adherence to best security practices and controls.
• Design and implement security baseline controls for cloud services, integrating them into the CI/CD pipeline.
• Build and deliver policies as code, automating security controls and best practices across cloud environments.
• Review and approve code and configuration changes with security implications, including IAM roles, policies, and security groups.
• Serve as the cloud security subject matter expert within the Cloud Engineering team and collaborate on IaaS, PaaS, and SaaS implementations.

AI & Machine Learning Security

• Define and implement a comprehensive security framework for AI/ML systems, covering data ingestion, training, deployment, and monitoring phases.
• Assess and mitigate AI-specific threats such as adversarial attacks, model inversion, data poisoning, prompt injection, and model theft.
• Evaluate and secure AI/ML platforms and tools (e.g., SageMaker, Azure ML, Hugging Face, OpenAI APIs) against organizational risk standards.
• Collaborate with data science and AI engineering teams to integrate security controls into MLOps pipelines, ensuring model integrity and auditability.
• Monitor emerging AI threat landscapes and regulatory developments, translating these into actionable organizational controls.

Data Security

• Implement and manage data security posture management tools to monitor sensitive data exposure across cloud environments.
• Establish controls for structured and unstructured data stores, including databases, data lakes, and warehouses.
• Promote data-centric security practices within application development and analytics teams.

General Security Leadership

• Provide expertise on architecture, authentication, and systems security, understanding the engineering stack and data flow.
• Lead cybersecurity risk assessments of new and existing technologies, including AI/ML systems and data platforms.
• Provide pragmatic cybersecurity guidance during major technology initiatives to balance security and innovation.
• Assist in investigating and remediating security incidents, including AI model compromises and data breaches.
• Work closely with security, product, and development teams to assess risks and recommend solutions in cloud, AI, and data environments.

Your Mindset

• You are a self-starter, driven, and capable of managing multiple projects and priorities effectively.
• You are passionate about fostering a DevSecOps and MLSecOps culture in a fast-paced environment.
• You understand the intersection of security, AI, and data, actively seeking to build bridges between these disciplines.
• You are eager to