Cloud Infrastructure Architect

We are seeking candidates with over 8 years of experience for the role described below. You should have a minimum of 8 years of experience in designing, implementing, and maintaining infrastructure solutions. Additionally, you should have worked on at least 5 projects involving enterprise-level cloud architecture and implementation. Your expertise should extend to designing and implementing large-scale microservices architectures, distributed systems, and integration architectures. You should also have hands-on experience in large-scale cloud migration projects. Setting up infrastructure for ML workloads, including training, inference, and GPU/TPU provisioning, should be within your skill set. Your experience in data center operations, specifically in implementing and supporting private and hybrid cloud environments, is essential. Proficiency with VMware technologies like vSphere, ESXi, and vCenter is required. You should also possess hands-on expertise in infrastructure domains such as networking, authentication, compute, and storage. Responding to RFPs, preparing solution designs, and performing estimations and costing should be familiar tasks for you. Your knowledge of Docker and Kubernetes, along with experience deploying ML workloads, is crucial. You should be proficient in Infrastructure as Code (IaC) using tools like Ansible, Terraform, ARM Templates, and CloudFormation. A good understanding of SQL and NoSQL databases is necessary. Deep expertise in DevOps practices, containerization, and CI/CD pipelines is expected. Experience with monitoring tools such as Nagios, Splunk, New Relic, or Prometheus is beneficial. You should have worked on projects with compliance requirements like GDPR, PCI DSS, and HIPAA. A strong technical knowledge of cloud technologies and virtualization platforms (e.g., VMware, Hyper-V, Cisco, Microsoft, EMC, AWS) is also required. Your responsibilities will include designing, developing, and maintaining scalable cloud infrastructure solutions. You will lead cloud adoption strategies, migration roadmaps, and workload assessments. Providing infrastructure expertise to design cloud-native and on-premise solution architectures is part of the role. Architecting infrastructure solutions for AI/ML platforms, including training, inference, pipelines, and GPU/TPU setups, is also a key responsibility. Ensuring infrastructure security, compliance, and adherence to industry best practices is essential. Designing and implementing new capabilities to address gaps and provide an integrated, end-to-end, scalable service is part of the job scope. Collaboration with external vendors, partners, and stakeholders to ensure successful integration and implementation of infrastructure solutions is also expected. Candidates with AWS/Azure/GCP Architect Certifications and Kubernetes Certifications (CKA/CKAD) are preferred for this role.,