Senior AI Cloud Security Engineer

A Senior AI Cloud Security Engineer is responsible for building automating and enforcing security controls across cloud infrastructure and AI platforms. This role focuses on engineering secure-by-default systems integrating security into development workflows and protecting enterprise AI initiatives.

This job description is not a comprehensive listing of all job duties required for this role. We reserve the right to change these duties or assign additional duties at any time with or without notice.

The Security AI Cloud Security Engineer is responsible for designing implementing and automating security controls across cloud and AI environments ensuring secure-by-default architecture continuous compliance and protection against evolving threats. This includes:

• Implement and operate AI Security Posture Management (AI SPM) solutions including Cloud security posture management to continuously assess detect and remediate risks across AI and cloud environments

• Secure AI and Generative AI workloads including model pipelines training data inference APIs and LLM integrations against threats such as prompt injection data leakage model abuse and adversarial attacks

• Design and implement AI SPM controls to provide visibility into AI assets monitor model usage and access patterns enforce security guardrails and manage AI risks across the full lifecycle

• Embed security into CI/CD and MLOps pipelines (DevSecOps) using automated controls such as SAST/DAST IaC scanning secrets detection and compliance enforcement gates

• Develop and maintain security policies and policy-as-code frameworks (e.g. Azure Policy) to enforce governance regulatory compliance and responsible AI usage

• Engineer monitoring detection and response capabilities for cloud and AI systems integrating telemetry with SIEM/SOAR platforms for centralized visibility and automated response

• Perform security testing and validation across cloud application API and AI layers including AI-specific scenarios such as prompt injection and model misuse prior to production deployment

• Automate security operations through scripting and tooling (e.g. Python PowerShell) to improve efficiency scalability and consistency of controls

• Conduct risk assessments threat modeling and security reviews for cloud infrastructure and AI systems to identify vulnerabilities and implement mitigation strategies

• Collaborate with AI teams and security stakeholders to drive secure-by-design architectures and enable scalable governed AI adoption

• Research and stay current on emerging security standards AI security trends threat vectors and vulnerabilities including risks specific to Generative AI LLMs and ML systems

• Hands-on Experience With AI security tools and Understanding of LLM and AI-specific threats.

• Develop document and disseminate security guidelines remediation playbooks and hardened baselines for both cloud and AI systems

• Collaborate with Penetration Testing teams to perform security assessments across cloud platforms and AI systems including adversarial testing prompt injection simulations and AI misuse scenarios

• Partner with Security Operations (SOC) and Incident Response teams to ensure effectiveness of preventive detective and responsive controls for cloud and AI environments

• Implement and tune monitoring and detection controls for cloud infrastructure and AI systems and support response to AI-related threats such as model abuse or data leakage

• Build and maintain automation to streamline security tasks testing validation workflows and remediation processes across cloud and AI pipelines

• Configure integrate and maintain security tools and technologies for AI SPM solutions Model and Agent security solution ensuring comprehensive coverage across cloud and AI workloads

• Continuously evaluate and recommend proactive security improvements based on evolving cloud and AI threat landscapes including enhancements to AI governance and security posture

• Provide guidance to engineering and AI teams on secure AI development practices responsible AI usage and compliance with AI governance frameworks

• Minimum 7-8 years IT industry experience

• Minimum 5 years of experience in cloud and security engineering with strong hands-on expertise in Azure or similar cloud platforms

• Required experience in AI Security and AI SPM including securing AI and Generative AI systems and managing risks such as prompt injection data leakage and model abuse

• Proven experience with CSPM CWP and IaC and implementing secure cloud architectures

• Strong understanding of DevSecOps practices including CI/CD security SAST/DAST IaC scanning and automation (Python/PowerShell)

• Experience developing and enforcing security policies and policy-as-code frameworks aligned with standards like NIST ISO and CIS

• Knowledge of security monitoring SIEM/SOAR and incident response for cloud and AI environments

• Experience with security testing threat modeling and risk assessments

• Strong collaboration and communication skills with the ability to work across cloud AI and security teams