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. 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 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 fastpaced, 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 highperforming 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 710 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 vendorspecific AI security training) or data security (e.g., CDPSE, CIPP) Cloud Security Demonstrated knowledge of cloud architecture, cloud operations, cloudbased identity and access management, security automation, and orchestration Extensive experience with cloudnative 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, ISO27001, ISO27017, and NISTCSF 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 Top10 for LLMs, MITRE ATLAS, and NIST AI Risk Management Framework (AIRMF) 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 largescale data environments Familiarity with data privacy regulations (e.g., PIPEDA, GDPR, CCPA) and their technical implementation requirements Experience securing cloudbased 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 relationshipbuilding skills with the ability to clearly articulate complex security concepts across a diverse corporate culture Ability to lead indepth workshops across a broad range of topics including cloud compliance, AI risk, and data governance Strong ability to influence decisionmaking at senior leadership levels Other Skills Strong interpersonal, communication, and leadership skills A critical thinker with strong research, analytical, and problemsolving skills Selfmotivated 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 Canadas largest financial institutions at a time when these domains are converging and rapidly evolving. You will work at the forefront of emerging threats, influence enterprisewide security standards, and collaborate with worldclass teams across technology, risk, and innovation. Job Type Fulltime Salary $103,200.00 $192,000.00 Pay Type Salaried Compensation & Benefits The above represents BMO Financial Groups 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. BMO Financial Groups total compensation package will vary based on the pay type of the position and may include performancebased incentives, discretionary bonuses, and 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 Accommodations BMO is committed to an inclusive, equitable and accessible workplace. By learning from each others 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. #J-18808-Ljbffr
Job Title
Senior Cloud Security Engineer