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
Responsibilities
- Define and drive enterprise architecture roadmaps, cloud strategies, and target-state architectures to achieve measurable business outcomes
- Design and govern scalable cloud and hybrid infrastructure solutions, ensuring robust architecture and operational excellence across Azure, AWS, and GCP
- Develop and maintain reference architectures, landing zones, modernization frameworks, and solution blueprints that accelerate enterprise transformation
- 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 within the Cloud, AI & Infrastructure Center of Excellence
- 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 to ensure solutions are secure, scalable, and cost optimized
- 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
Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a closely related discipline
- AWS Certified Solutions Architect, Azure Solutions Architect, or Google Professional Cloud Architect certification
Required Skills
- 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
Preferred Skills
- 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
Candidates should demonstrate the below listed critical leadership qualities:
Customer Advocacy – Lead with the client's business priorities and build relationships grounded in relevance, trust and measurable value.
Owner's Mindset – Take accountability for the territory, pipeline and results; approach every target account with a clear ambition to build a meaningful Brillio franchise.
Innovation Ethos – Bring new ideas and perspectives that challenge conventional thinking and create reasons for clients to engage.
Execution with Pace – Maintain urgency, discipline and momentum from initial access through contract closure.
Big Picture Thinking – Connect individual opportunities to broader client transformation agendas and Brillio's long term growth strategy.
Winning Through Teams – Mobilize the best of Brillio and its ecosystem to create differentiated propositions and win together.