Senior Cloud Security Engineer

Application Deadline:

05/28/2026

Address:

320 S Canal Street

Job Family Group:

Technology

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. We need someone who can 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.

We are looking for someone who has a high level of technical security expertise and who takes seriously the responsibility of monitoring, detecting, protecting, and maintaining the security of data, AI/ML systems, cloud platforms, and networks.

You are a leader with a strong technical background. You have demonstrated strength in:

• Developing and implementing secure cloud and AI/ML architectures using a risk-based cybersecurity and data privacy strategy

• Defining security patterns, roadmaps, and operating models that leverage collaboration

• Facilitating industry-standard information security governance

• Advising senior leadership on cybersecurity, AI risk, and privacy risks, threats, and investment strategies

• Documenting appropriate policies and procedures to manage information security risks, including those unique to AI/ML systems and sensitive data assets

As a qualified candidate, you will be part of the team driving BMO's Cloud, AI, and Data Security implementation. As a member of this team, you should possess the ability to inspire yourself and all of our team. Based on your previous experiences, you will inject new knowledge and skills into an already high-performing team, thus elevating our efforts to new heights.

Your Responsibilities

Cloud Security

• Assess, design, implement, automate, and document security solutions, controls, and processes for Amazon Web Services (AWS) and Microsoft Azure cloud platforms

• Develop and maintain security patterns for cloud platforms and services; assess all cloud patterns to ensure adherence to best security practices and controls

• Design and implement security baseline controls for Cloud Services for integration into the CI/CD process

• Build and deliver policies as code, automating security controls and best practices

• Review and approve code and changes with security implications (e.g., IAM Roles and Policies, Security Groups, etc.)

• Be the cloud security subject matter expert for the Cloud Engineering group and its partners in any IaaS, PaaS, and SaaS implementations

AI & Machine Learning Security

• Define and implement a security framework for AI/ML systems, covering the full model lifecycle from data ingestion and training to deployment and monitoring

• Assess and mitigate AI-specific threats including adversarial attacks, model inversion, data poisoning, prompt injection, and model theft

• Evaluate and secure AI/ML platforms and tools (e.g., Amazon SageMaker, Azure Machine Learning, 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, access controls, and auditability

• Monitor emerging AI threat landscapes and regulatory developments (e.g., EU AI Act, NIST AI RMF) and translate these into actionable organizational controls

Data Security

• Implement and manage data security posture management (DSPM) tools to continuously monitor sensitive data exposure across cloud environments

• Establish controls for structured and unstructured data stores, including databases, data lakes, data warehouses (e.g., Snowflake, AWS S3, Azure Data Lake), and file sharing platforms

• Drive the adoption of data-centric security practices within application development and analytics teams

General Security Leadership

• Provide subject matter expertise on architecture, authentication, and systems security based on a clear understanding of the engineering stack, services, and data flow

• Lead focused and continuous cybersecurity risk assessments of new and existing technologies - including AI/ML systems and data platforms - to identify risks and appropriate controls that balance security and operability