Job description

Application Deadline: 10/29/2026 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 Provide effective and pragmatic cybersecurity guidance upfront in major technology projects to enable the business to innovate securely Assist in the investigation and remediation of security incidents and issues, including those involving AI model compromise or data breaches Work closely with Information Security, product, and software development teams to assess cybersecurity risk and recommend solutions in cloud, AI, and data environments Your Mindset You are a self-starter , driven, and can handle multiple projects and priorities You are passionate about driving the DevSecOps and MLSecOps mindset and culture in a fast-paced, challenging environment where you get the opportunity to work with the latest tools and technologies You understand the intersection of security, AI, and data , and actively seek to build bridges between these disciplines You are actively looking to improve the solutions you implement, understand the efficacy of collaboration, and are keen to work in a team of CI/CD, infrastructure, AI, and data specialists You are energized by the rapidly evolving AI threat landscape and bring intellectual curiosity and practical judgment to navigating ambiguity As a member of this team, you will inject new knowledge and skills into an already high-performing team, elevating our collective efforts to new heights Required Core Skills Foundational A university degree in Engineering, Computer Science, Information Technology , or a related field 7-10 years of experience developing and implementing security architectures and/or engineering, with demonstrated breadth across cloud, data, and/or AI security domains Security certifications such as CISSP, CCSP, CCSK , or any Cloud Security Specialty certification (e.g., AWS Certified Security Specialty, Microsoft Certified: Azure Security Engineer Associate) Emerging/preferred: Certifications or demonstrated knowledge in AI security (e.g., CDAI, CompTIA AI , or equivalent vendor-specific AI security training) or data security (e.g., CDPSE, CIPP) Cloud Security Demonstrated knowledge of cloud architecture, cloud operations, cloud-based identity and access management, security automation, and orchestration Extensive experience with cloud-native security solutions and tools (e.g., AWS Security Hub, AWS GuardDuty, Microsoft Defender for Cloud, Azure Sentinel) Knowledge of technical security control environments and compliance frameworks including CSA CCM, ISO 27001, ISO 27017, and NIST CSF AI & ML Security Working knowledge of AI/ML development frameworks and platforms (e.g., TensorFlow, PyTorch, SageMaker, Azure ML) and associated security risks Familiarity with the OWASP Top 10 for LLMs , MITRE ATLAS , and NIST AI Risk Management Framework (AI RMF) Understanding of MLOps pipeline security , including securing model registries, feature stores, training environments, and inference endpoints Knowledge of Generative AI security risks , including prompt injection, jailbreaking, data leakage via LLMs, and supply chain risks in AI model dependencies Data Security Experience implementing data loss prevention (DLP) , data classification , and data access governance solutions in enterprise environments Knowledge of DSPM tools and practices Understanding of data encryption at rest and in transit , tokenization, and key management for large-scale data environments Familiarity with data privacy regulations (e.g., PIPEDA, GDPR, CCPA) and their technical implementation requirements Experience securing cloud-based data platforms such as Snowflake, Databricks, AWS Redshift, Azure Synapse, or equivalent Technical Skills Firm grasp of networking protocols and operations ; comfortable with packet analysis tools such as Wireshark, Burp Suite, nmap, Nessus, and Metasploit Knowledge of theoretical and applied cryptography , key management, and cryptographic algorithms (RSA, AES, TLS, PKI, etc.) Knowledge of Identity and Access Management (IAM) concepts including SSO, SAML, federated identity, RBAC, and OAuth/OIDC Strong scripting and programming skills with experience in Python, PowerShell, Bash, Node.js , and API/webhook development Experience with Infrastructure as Code (IaC) security scanning tools (e.g., Checkov, tfsec, Prisma Cloud) Interpersonal & Leadership Demonstrable internal and external relationship-building skills with the ability to clearly articulate complex security concepts across a diverse corporate culture Ability to lead in-depth workshops across a broad range of topics including cloud compliance, AI risk, and data governance Strong ability to influence decision-making at senior leadership levels Other Skills Strong interpersonal, communication, and leadership skills A critical thinker with strong research, analytical, and problem-solving skills Self-motivated with a positive attitude and an ability to work independently and within a team Ability to communicate complex technical concepts to a broad range of internal and external stakeholders, including business, legal, compliance, and technology leaders Strong time management skills with the ability to manage multiple workstreams and mentor less experienced team members Why Join Us? This is a rare opportunity to shape the cloud, AI, and data security strategy of one of Canada s largest financial institutions at a time when these domains are converging and rapidly evolving. You will work at the forefront of emerging threats, influence enterprise-wide security standards, and collaborate with world-class teams across technology, risk, and innovation. Salary : $122,400.00 - $228,000.00 Pay Type: Salaried The above represents BMO Financial Group’s pay range and type. Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group’s expected target for the first year in this position. BMO Financial Group’s total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit: jobs.bmo.com About Us At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world. As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one – for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we’ll help you gain valuable experience, and broaden your skillset. To find out more visit us at jobs.bmo.com BMO is proud to be an equal employment opportunity employer. We evaluate applicants without regard to race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or any other legally protected characteristics. We also consider applicants with criminal histories, consistent with applicable federal, state and local law. BMO is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process, please send an e-mail to BMOCareers.Support bmo.com and let us know the nature of your request and your contact information. Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.

Requirements

Must-haves

320 S Canal Street
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
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

Nice-to-haves

Emerging/preferred: Certifications or demonstrated knowledge in AI security (e.g., CDAI, CompTIA AI , or equivalent vendor-specific AI security training) or data security (e.g., CDPSE, CIPP)

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiawsazuremlci/cdmachine learningrestpythonnode.jsapi

Platform: workday
Effort: long

Benefits

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Health Insurance

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