Staff Cloud Security Engineer

Cloud Security Engineering

• Design, implement, automate, and maintain security architectures, controls, and processes across AWS and Microsoft Azure environments

• Develop and maintain cloud security reference architectures, patterns, and guardrails aligned with industry best practices and Bloom Energy security standards

• Build and operationalize security baseline controls integrated into CI/CD pipelines and Infrastructure-as-Code deployments

• Implement policy-as-code and automated compliance validation across cloud environments

• Review and approve security-sensitive infrastructure and application changes, including IAM policies, network security controls, secrets management, and cloud-native services

• Serve as the cloud security subject matter expert supporting enterprise cloud transformation initiatives across IaaS, PaaS, and SaaS platforms

AI & Machine Learning Security

• Define and implement security frameworks for AI/ML systems across the full model lifecycle, including data ingestion, model training, deployment, and monitoring

• Assess and mitigate emerging AI security risks such as adversarial attacks, prompt injection, model theft, model inversion, and data poisoning

• Secure AI/ML platforms and services including Amazon SageMaker, Bedrock, Azure Machine Learning, OpenAI APIs, and other enterprise AI tooling

• Collaborate with AI engineering and data science teams to integrate security controls into MLOps pipelines and AI governance processes

• Monitor evolving AI regulations, standards, and frameworks including NIST AI RMF and global AI governance initiatives, translating them into actionable controls and engineering practices

Data Security

• Implement and manage Data Security Posture Management (DSPM) capabilities to identify and reduce sensitive data exposure across cloud environments

• Design and enforce controls for structured and unstructured data platforms including databases, data lakes, warehouses, object storage, and analytics platforms such as AWS S3.

• Drive adoption of data-centric security controls including encryption, tokenization, data classification, retention, and access governance

• Partner with application and analytics teams to embed secure data handling practices into engineering workflows

Security Architecture & Leadership

• Provide deep technical expertise across cloud, AI, infrastructure, identity, and application security domains

• Lead security assessments and threat modeling exercises for cloud services, AI/ML platforms, enterprise applications, and emerging technologies

• Enable secure innovation by partnering with engineering teams early in the design and development lifecycle

• Support incident response, investigation, and remediation activities related to cloud, AI, and data security events

• Collaborate closely with Information and OT Security, Infrastructure, Product Engineering, and Enterprise Architecture teams to drive secure technology adoption across the organization

• Contribute to the development of security standards, policies, and operational procedures aligned with business and regulatory requirements

What You Bring

Mindset

• Self-starter with strong ownership mentality and ability to manage multiple priorities in a dynamic environment

• Passion for DevSecOps, automation, and engineering scalable security solutions

• Strong curiosity and practical understanding of the evolving AI threat landscape and modern cloud-native technologies

• Collaborative mindset with ability to work effectively across engineering, infrastructure, AI, data, and security teams

• Strong communication skills with the ability to influence technical and business stakeholders

• Desire to continuously improve security maturity while enabling business agility and innovation

Qualifications

Required

• Bachelor's degree in computer science, Engineering, Information Technology, Cybersecurity, or related field

• 10+ years of experience in security engineering, cloud security architecture, or cybersecurity operations

• Strong hands-on expertise with AWS and/or Microsoft Azure security services and cloud-native architectures

• Experience implementing security automation within CI/CD and Infrastructure-as-Code environments

• Deep understanding of IAM, network security, encryption, secrets management, logging, monitoring, and threat detection

• Experience securing enterprise data platforms and modern cloud-native applications

• Strong knowledge of security frameworks and best practices including NIST, CIS, Zero Trust, and secure SDLC principles

Preferred

• Experience securing AI/ML platforms, GenAI services, or MLOps pipelines

• Familiarity with AI governance, AI security risks, and emerging regulatory frameworks

• Experience with DSPM, CSPM, CNAPP, SIEM, SOAR, and modern cloud security tooling

• Security certifications such as CISSP, CCSP, CCSK, AWS Certified Security Specialty, or Microsoft Certified: Azure Security Engineer Associate

• Preferred additional certifications or training in AI security or data privacy/security domains (e.g., CDPSE, CIPP, AI security certifications)