BR
BrillioEnterprise Architect - R01571847
LocationSan Francisco, California, United States
Work modehybrid
SeniorityLead
Experience18–21 yrs
DepartmentInfrastructure Engineering, Infrastructure Engineering : Infrastructure Engineering
Company size5,001–10,000 people
PostedSep 28, 2026 · 2w ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
18 to 21 years of experience, including extensive leadership in enterprise architecture
Leadership in enterprise architecture
Experience with Azure, AWS, and GCP cloud platforms
Define and drive enterprise architecture roadmaps, cloud strategies, and target-state architectures
Design and govern scalable cloud and hybrid infrastructure solutions
Develop and maintain reference architectures, landing zones, modernization frameworks, and solution blueprints
Advise CXOs and senior stakeholders on technology transformation initiatives, responsible AI adoption, and modernization strategies
Establish standards, best practices, governance frameworks, and reusable solution accelerators
Lead cloud migration, modernization, and platform engineering programs, driving adoption of cloud-native architectures, automation, DevOps, containers, and infrastructure-as-code practices
Implement cloud governance, security, compliance, and FinOps strategies
Design and establish resiliency patterns for mission-critical AI workloads
Enterprise architecture methodologies and frameworks (e.g., TOGAF, Zachman)
Expert-level experience with Azure, AWS, and GCP cloud platforms
Cloud migration, modernization, and platform engineering expertise
Hands-on experience with infrastructure-as-code tools such as Terraform and Azure Resource Manager
Cloud-native architectures, containerization (e.g., Kubernetes, Docker), and automation frameworks
Cloud governance, security, compliance, and FinOps strategies
Designing AI-enabled infrastructure solutions and operational resilience patterns
Developing solution blueprints, reference architectures, and modernization frameworks
Establishing observability, operational readiness, and controls for AI workloads
Bachelor's degree in Computer Science, Information Technology, Engineering, or a closely related discipline
Multi-cloud integration and provider-independent architecture patterns
Advanced AI operational controls including model drift, auditability, and human-in-the-loop safeguards
Business continuity and disaster recovery frameworks for AI workloads
Developing reusable IP assets and solution accelerators
Cloud platform engineering for large-scale enterprise transformations
Skills
Azure
AWS
GCP
Terraform
Azure Resource Manager
Kubernetes
Docker
TOGAF
DevOps
Enterprise Architect
Primary Skills
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Business Analyst, Project Management
Specialization
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Project Management: Enterprise Architect, Security
Job requirements
•
Experience Range: 18 to 21 years of experience, including extensive leadership in enterprise architecture, cloud infrastructure, and technology consulting across Azure, AWS, and GCP environments Key Responsibilities: 1. Define and drive enterprise architecture roadmaps, cloud strategies, and target-state architectures to achieve measurable business outcomes 2. Design and govern scalable cloud and hybrid infrastructure solutions, ensuring robust architecture and operational excellence across Azure, AWS, and GCP 3. Develop and maintain reference architectures, landing zones, modernization frameworks, and solution blueprints that accelerate enterprise transformation 4. Advise CXOs and senior stakeholders on technology transformation initiatives, responsible AI adoption, and modernization strategies 5. Establish standards, best practices, governance frameworks, and reusable solution accelerators within the Cloud, AI & Infrastructure Center of Excellence 6. Lead cloud migration, modernization, and platform engineering programs, driving adoption of cloud-native architectures, automation, DevOps, containers, and infrastructure-as-code practices 7. Implement cloud governance, security, compliance, and FinOps strategies to ensure solutions are secure, scalable, and cost optimized 8. Design and establish resiliency patterns for mission-critical AI workloads, including business continuity, operational readiness, and controls for model and provider failure, with clear metrics for reliability and performance Required Skills: 1. Enterprise architecture methodologies and frameworks (e.g., TOGAF, Zachman) 2. Expert-level experience with Azure, AWS, and GCP cloud platforms 3. Cloud migration, modernization, and platform engineering expertise 4. Hands-on experience with infrastructure-as-code tools such as Terraform and Azure Resource Manager 5. Cloud-native architectures, containerization (e.g., Kubernetes, Docker), and automation frameworks 6. Cloud governance, security, compliance, and FinOps strategies 7. Designing AI-enabled infrastructure solutions and operational resilience patterns 8. Developing solution blueprints, reference architectures, and modernization frameworks 9. Establishing observability, operational readiness, and controls for AI workloads Preferred Skills: 1. Multi-cloud integration and provider-independent architecture patterns 2. Advanced AI operational controls including model drift, auditability, and human-in-the-loop safeguards 3. Business continuity and disaster recovery frameworks for AI workloads 4. Developing reusable IP assets and solution accelerators 5. Cloud platform engineering for large-scale enterprise transformations Desired Qualifications: 1. Bachelor’s degree in Computer Science, Information Technology, Engineering, or a closely related discipline 2. AWS Certified Solutions Architect, Azure Solutions Architect, or Google Professional Cloud Architect certification 3. TOGAF or equivalent enterprise architecture framework certification