Weekend Database Security Engineer Jobs in Chicago, IL

Job Summary:
BMO U.S. is seeking a Principal Cloud Security Engineer to design and implement security solutions for cloud, AI, and data systems. The role involves establishing security governance, providing assurance to management, and embedding controls in operational practices with a focus on automation.
Responsibilities:
• 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
• 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
Qualifications:
Required:
• 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)
• 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
• 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)
• 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
• 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
Preferred:
• 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)
Company:
We’re a bank, but there’s more to it than that. We're a top ten bank in North America and have been serving our customers since 1817. Founded in 1882, the company is headquartered in Chicago, USA, with a team of 5001-10000 employees. The company is currently Late Stage.