Senior Cloud Security Engineer

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

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

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

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

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)

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

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

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

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

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.

Job Type: Full-time

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: https://jobs.bmo.com/global/en/Total-Rewards

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 https://jobs.bmo.com/ca/en .

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.

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.