The Cloud & AI Infrastructure Architect shall bring considerable experience in the areas of cloud economics, FinOps Operating model and cloud cost optimization. The Lead should be able to :
- Develop AIready 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 endtoend 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, AIoptimized compute clusters).
- Collaborate with Sales, Industry Leads, and Delivery to generate leads, engage and craft winning propositions
- Conduct Csuite conversations on AI cloud strategy, value cases, and futureready architecture pathways.
- 7+ 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 clientfacing experience.
- Experience in technical pre-sales and deal shaping is a must.
Other Skills Required
- Excellent verbal and written communication and presentation skills.
- Willingness to travel for client engagements/ presentations (30% of the time)
