Principal AI & Cloud Security Engineer (Remote only within WA, ID, OR)

Banner Bank

19d•$135,000 - $178,000•Remote

About The Position

This senior individual contributor role sets the strategic direction for AI and cloud security, helping development, infrastructure, and security teams build innovative solutions that are secure, resilient, and compliant. If you're passionate about emerging technologies, security architecture, and influencing enterprise-wide standards, we'd love to hear from you. In this role you'll Define and lead the enterprise security strategy and architecture for AI-powered systems and Azure cloud environments, including identity, network security, data protection, and secure cloud and hybrid designs. Establish and govern security controls, guardrails, and runtime protections for agentic AI workflows, including tools such as Claude, GitHub Copilot, and custom AI agents. Lead threat modeling efforts for AI systems and Azure-hosted workloads, identifying and mitigating risks associated with adversarial inputs, cloud vulnerabilities, autonomous agents, and emerging attack vectors. Evaluate AI-generated and cloud-integrated code for security, quality, correctness, and performance, and define enterprise standards for secure code review practices. Architect and oversee security tooling and monitoring capabilities that evaluate, monitor, and harden AI agents and Azure resources at scale using technologies such as Microsoft Defender for Cloud, Azure Monitor, and Microsoft Sentinel. Embed security governance into the software development lifecycle and Azure DevSecOps pipelines through Security Posture Management, Azure Policy, Key Vault, and Infrastructure-as-Code standards. Research emerging AI and cloud security threats, regulations, and industry trends, translating insights into actionable strategies and enterprise security improvements. Mentor and influence engineering teams on secure AI adoption, cloud security best practices, and enterprise security standards.

Requirements

Bachelor's degree in Computer Science, Cybersecurity, Information Technology, Engineering, or a related field (Required). An equivalent combination of education and experience can be considered in lieu of a degree.
8+ years of experience in security engineering, secure SDLC, threat modeling, and Azure cloud security, including designing and governing security controls for AI/ML, generative AI, and agentic systems in enterprise cloud environments (Required).

Nice To Haves

Master's degree (Preferred).
Experience within financial services or banking environments (Preferred).
Industry-recognized security certifications such as CISSP, Azure Security Engineer, GIAC, or similar credentials (Preferred).
You communicate complex security concepts clearly and effectively to both technical and non-technical audiences.
You excel at analyzing emerging threats and translating risks into practical enterprise security strategies.
You bring deep expertise in Azure cloud security, including Microsoft Entra ID, network security, data protection, defense-in-depth, and zero-trust architecture.
You understand how to secure and govern AI/ML platforms, large language models, and agentic AI architectures.
You have hands-on experience evaluating AI-generated outputs and implementing guardrails, validation controls, and runtime protections.
You possess advanced secure coding and DevSecOps experience across modern programming languages such as Python, Go, Rust, or C/C++.
You have strong knowledge of Cloud Security Posture Management and Infrastructure-as-Code solutions including Bicep, ARM, and Terraform.
You understand regulatory, risk, and security considerations common within financial services environments.

Responsibilities

Define and lead the enterprise security strategy and architecture for AI-powered systems and Azure cloud environments, including identity, network security, data protection, and secure cloud and hybrid designs.
Establish and govern security controls, guardrails, and runtime protections for agentic AI workflows, including tools such as Claude, GitHub Copilot, and custom AI agents.
Lead threat modeling efforts for AI systems and Azure-hosted workloads, identifying and mitigating risks associated with adversarial inputs, cloud vulnerabilities, autonomous agents, and emerging attack vectors.
Evaluate AI-generated and cloud-integrated code for security, quality, correctness, and performance, and define enterprise standards for secure code review practices.
Architect and oversee security tooling and monitoring capabilities that evaluate, monitor, and harden AI agents and Azure resources at scale using technologies such as Microsoft Defender for Cloud, Azure Monitor, and Microsoft Sentinel.
Embed security governance into the software development lifecycle and Azure DevSecOps pipelines through Security Posture Management, Azure Policy, Key Vault, and Infrastructure-as-Code standards.
Research emerging AI and cloud security threats, regulations, and industry trends, translating insights into actionable strategies and enterprise security improvements.
Mentor and influence engineering teams on secure AI adoption, cloud security best practices, and enterprise security standards.