Principal Cloud Security Engineer

Requirements:

• We require a university degree in Engineering, Computer Science, Information Technology, or a related discipline.
• We require 7 to 10 years of experience building and applying security architectures or engineering solutions, with breadth across cloud, data, and/or AI security.
• We require recognized security certifications such as CISSP, CCSP, CCSK, or a cloud security specialty credential such as AWS Certified Security Specialty or Microsoft Certified: Azure Security Engineer Associate.
• We value emerging knowledge or certifications in AI security, such as CDAI, CompTIA AI+, or equivalent vendor-specific training, as well as data security credentials such as CDPSE or CIPP.
• We require strong knowledge of cloud architecture, cloud operations, identity and access management, security automation, and orchestration.
• We require hands-on experience with cloud-native security tools and services such as AWS Security Hub, AWS GuardDuty, Microsoft Defender for Cloud, and Azure Sentinel.
• We require familiarity with security and compliance frameworks including CSA CCM, ISO 27001, ISO 27017, and NIST CSF.
• We require working knowledge of AI/ML platforms and development frameworks such as TensorFlow, PyTorch, SageMaker, and Azure ML, along with the related security considerations.
• We require understanding of AI threat models, including prompt injection, model theft, model inversion, data poisoning, adversarial attacks, and supply chain risk.
• We require familiarity with the OWASP Top 10 for LLMs, MITRE ATLAS, and the NIST AI Risk Management Framework.
• We require experience with data loss prevention, data classification, data access governance, and DSPM practices.
• We require knowledge of encryption at rest and in transit, tokenization, and key management in large-scale data environments.
• We require awareness of privacy laws such as PIPEDA, GDPR, and CCPA and how to implement technical controls aligned to them.
• We require experience securing cloud-based data platforms such as Snowflake, Databricks, AWS Redshift, or Azure Synapse.
• We require solid networking knowledge and familiarity with tools such as Wireshark, Burp Suite, nmap, Nessus, and Metasploit.
• We require understanding of cryptography, key management, and common algorithms and protocols such as RSA, AES, TLS, and PKI.
• We require strong IAM knowledge, including SSO, SAML, federated identity, RBAC, and OAuth/OIDC.
• We require strong scripting and development capability in Python, PowerShell, Bash, Node.js, and API or webhook development.
• We require experience using Infrastructure as Code security scanning tools such as Checkov, tfsec, or Prisma Cloud.
• We require excellent communication, relationship-building, and facilitation skills, with the ability to explain complex security topics clearly across a broad organization.
• We require a self-starter mindset, the ability to manage multiple priorities, and the confidence to lead workshops and cross-functional discussions.

Responsibilities:

• We assess, design, implement, automate, and document security solutions, controls, and processes for AWS and Microsoft Azure environments.
• We create and maintain cloud security patterns and verify that cloud designs follow best practices and control requirements.
• We build security baseline controls for cloud services and embed them into CI/CD pipelines.
• We develop policies as code and automate security safeguards and standards.
• We review and approve security-relevant code and configuration changes, including IAM roles, policies, and security groups.
• We serve as the cloud security subject matter expert for the Cloud Engineering team and its partners across IaaS, PaaS, and SaaS implementations.
• We define and apply a security framework for AI/ML systems across the full model lifecycle, from data intake and training through deployment and monitoring.
• We identify and reduce AI-specific risks such as adversarial attacks, data poisoning, prompt injection, model theft, and model inversion.
• We evaluate and secure AI/ML platforms and tools against our organizational risk standards.
• We partner with data science and AI engineering teams to integrate security controls into MLOps workflows and preserve model integrity, access control, and auditability.
• We monitor evolving AI threats and regulatory developments and translate them into practical internal controls.
• We implement and operate DSPM tooling to track sensitive data exposure across cloud environments.
• We establish protections for structured and unstructured data stores, including databases, data lakes, data warehouses, and file-sharing platforms.
• We promote data-centric security practices within application development and analytics teams.
• We provide architecture, authentication, and systems security guidance based on a strong understanding of the engineering stack, services, and data flows.
• We lead ongoing cybersecurity risk assessments for new and existing technologies, including AI/ML systems and data platforms.
• We provide timely and pragmatic security advice on major technology initiatives so the business can innovate safely.
• We support investigation and remediation efforts for security incidents, including possible AI model compromise or data breaches.
• We collaborate closely with Information Security, product, and software development teams to evaluate risk and recommend solutions.

Technologies:

• AI
• API
• AWS
• Redshift
• Azure
• Bash
• CI/CD
• Cloud
• Cryptography
• Databricks
• DevSecOps
• IAM
• IaaS
• Support
• OWASP
• OAuth
• PaaS
• PowerShell
• Prisma
• PyTorch
• Python
• REST
• RBAC
• SAML
• Security
• Snowflake
• TensorFlow
• NodeJS
• DevOps
• Flow
• Machine Learning
• Web

More

We are driving the implementation of cloud, AI, and data security within our technology organization and are looking for a passionate senior professional to help shape that work. Our team operates at the intersection of security, cloud engineering, AI, and data, and we value collaboration, technical depth, and a proactive mindset. This is a chance to contribute to a high-performing group, strengthen our DevSecOps and MLSecOps culture, and help us keep pace with a rapidly changing threat landscape while building secure solutions across AWS, Azure, and modern AI/ML platforms.

last updated 43 week of 2026