Staff Cloud Security Engineer

CloudSecurityEngineering

• Design implement automate and maintainsecurityarchitectures controls and processes across AWS and Microsoft Azure environments

• Develop and maintaincloudsecurityreference architectures patterns and guardrails aligned with industry best practices and Bloom Energysecuritystandards

• Build and operationalizesecuritybaseline controls integrated into CI/CD pipelines and Infrastructure-as-Code deployments

• Implement policy-as-code and automated compliance validation acrosscloudenvironments

• Review and approvesecurity-sensitive infrastructure and application changes including IAM policies networksecuritycontrols secrets management andcloud-native services

• Serve as thecloudsecuritysubject matter expert supporting enterprisecloudtransformation initiatives across IaaS PaaS and SaaS platforms

AI & Machine LearningSecurity

• Define and implementsecurityframeworks for AI/ML systems across the full model lifecycle including data ingestion model training deployment and monitoring

• Assess and mitigate emerging AIsecurityrisks 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 integratesecuritycontrols 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

DataSecurity

• Implement and manage DataSecurityPosture Management (DSPM) capabilities to identify and reduce sensitive data exposure acrosscloudenvironments

• 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-centricsecuritycontrols including encryption tokenization data classification retention and access governance

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

SecurityArchitecture & Leadership

• Provide deep technical expertise acrosscloud AI infrastructure identity and applicationsecuritydomains

• Leadsecurityassessments and threat modeling exercises forcloudservices 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 tocloud AI and datasecurityevents

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

• Contribute to the development ofsecuritystandards 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 scalablesecuritysolutions

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

• Collaborative mindset with ability to work effectively across engineering infrastructure AI data andsecurityteams

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

• Desire to continuously improvesecuritymaturity while enabling business agility and innovation

Qualifications

Required

• Bachelors degree in computer science Engineering Information Technology Cybersecurity or related field

• 10 years of experience insecurityengineeringcloudsecurityarchitecture or cybersecurityoperations

• Strong hands-on expertise with AWS and/or Microsoft Azuresecurityservices andcloud-native architectures

• Experience implementingsecurityautomation within CI/CD and Infrastructure-as-Code environments

• Deep understanding of IAM networksecurity encryption secrets management logging monitoring and threat detection

• Experience securing enterprise data platforms and moderncloud-native applications

• Strong knowledge ofsecurityframeworks 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 AIsecurityrisks and emerging regulatory frameworks

• Experience with DSPM CSPM CNAPP SIEM SOAR and moderncloudsecuritytooling

• Securitycertifications such as CISSP CCSP CCSK AWS CertifiedSecuritySpecialty or Microsoft Certified: AzureSecurityEngineer Associate

• Preferred additional certifications or training in AIsecurityor data privacy/securitydomains (e.g. CDPSE CIPP AIsecuritycertifications)