Develop AI-ready cloud architectures covering GPU clusters, LLM hosting frameworks, distributed training, hybrid AI, and edge AI
Lead Cloud & AI modernization assessments, maturity evaluations, and capability gap identification
Define end-to-end AI infrastructure blueprints including data pipelines, vector stores, orchestrators, MLOps, and security layers
Design solution architectures, effort estimates, delivery models, and cost structures for AI cloud programs
Provide architectural governance during early delivery phases
Respond to RFPs/RFIs, write technical solution narratives, and participate in bid defenses
Create compelling demos, POVs, and prototypes showcasing unique capabilities (e.g., RAG pipelines, AI-optimized compute clusters)
Collaborate with Sales, Industry Leads, and Delivery to generate leads, engage and craft winning propositions

10+ years in cloud architecture
2+ years in AI infrastructure
Expertise in Azure AI Studio / Azure ML, AWS SageMaker / Bedrock and GCP Vertex AI
Infrastructure Modernization – Refactoring, replatforming, IaC and Secure Landing Zones
Kubernetes, GPU Scheduling, MLOps & LLMOps patterns
Identity & Access: Azure AD, AWS IAM, Okta
Monitoring: Prometheus, Grafana, Azure Monitor, CloudWatch
Experience with Solutioning for RFP responses and commercial models
Strong financial acumen for cloud AI TCO and GPU utilization optimization
Strong consulting and client-facing experience.

Infrastructure Architect

Key skills