Senior Cloud DevOps & AI Infrastructure Architect

Bosch Global Software Technologies Private Limited is a 100% owned subsidiary of Robert Bosch GmbH, one of the world's leading global supplier of technology and services, offering end-to-end Engineering, IT and Business Solutions. With over 27,000+ associates, it’s the largest software development center of Bosch, outside Germany, indicating that it is the Technology Powerhouse of Bosch in India with a global footprint and presence in the US, Europe and the Asia Pacific region.

As a Senior Cloud DevOps & AI Infrastructure Architect, you will design, build, and operate enterprise-scale cloud and on-premises infrastructure supporting advanced AI workloads.

Your responsibilities include:

• Design and implement multi-cloud reference architectures on AWS and Azure, applying Well-Architected principles across reliability, performance, security, and cost optimization pillars
• Architect and deploy fully automated, Infrastructure-as-Code (IaC) driven cloud provisioning using Terraform, Pulumi, Bicep, and CDK with CI/CD pipelines enabling zero-touch infrastructure deployments
• Build and operate multi-tenant platform infrastructure enforcing strict tenant isolation, resource quotas, namespace-level governance, and chargeback reporting mechanisms
• Design on-premises infrastructure for compute, networking, and storage, including bare-metal GPU/CPU clusters, HPC configurations, and hybrid-cloud connectivity solutions (VPN, Direct Connect, ExpressRoute)
• Define and implement platform scaling strategies combining horizontal auto-scaling, cluster autoscalers (EKS, AKS), and on-premises capacity planning to support elastic AI workloads
• Architect and maintain the Knowledge Fabric layer, integrating vector databases (Pinecone, Weaviate, pgvector), document stores, relational and graph databases, and structured metadata registries into unified, semantically searchable retrieval pipelines
• Develop infrastructure blueprints and platform services supporting diverse cloud-native workloads including microservices (service mesh, API gateway, event streaming), AI inference endpoints, AI model hosting (SageMaker, Azure ML, Triton), MCP servers, and data management pipelines

BE

8 to 12 Years