Cloud AI Platform Architect (Delhi)

Key Responsibilities: - AI Platform & Infrastructure Engineering and Architecture Leadership - Lead the design and implementation of enterprise AI platforms that support AI/ML, GenAI, Agentic AI and RAG workloads across hybrid and multi-cloud environments. - Architect scalable cloud-native AI foundations using AWS SageMaker and Bedrock, Azure ML and Azure OpenAI, GCP Vertex AI and enterprise Kubernetes platforms such as EKS, AKS and GKE. - Build secure and resilient infrastructure for AI model development, training, deployment and runtime operations including compute, GPU environments, storage, networking, secrets management and access control. - Design reusable platform services for model hosting, inference endpoints, vector databases, prompt orchestration, agent runtime support and enterprise API integration. - Establish platform observability with centralized logging, monitoring, tracing, telemetry, performance diagnostics and cost optimization for AI systems. - Enable secure AI platform controls with policy enforcement, access governance, auditability and support for Responsible AI, compliance and risk requirements. - Drive standardization of AI platform architecture through reusable patterns, landing zones, workplace templates and enterprise engineering best practices. - Client & Stakeholder Management - Serve as primary technical advisor to CxOs, account leadership teams and enterprise engineering stakeholders on AI platform strategy, cloud modernization and deployment architecture. - Conduct technical workshops demonstrating platform blueprints, deployment models, MLOps capabilities, observability approaches and AI operational readiness. - Bridge platform engineering with business strategy by translating complex infrastructure capabilities into scalable business outcomes and delivery roadmaps. - Build trusted relationships through hands-on PoC delivery, architecture discussions and strategic guidance on AI platform adoption - Cloud, Automation & Deployment .