Senior Cloud Security Engineer

Application Deadline:

07/29/2026

Address:

33 Dundas Street West

Job Family Group:

Technology

Description

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 . click apply for full job details