Senior Staff Consulting Architect - AI / Kubernetes

Hungry, Humble, Honest, with Heart. The Opportunity Are you a passionate innovator with a strong background in AI/Kubernetes infrastructure, excellent client-facing communication skills, and a relentless drive to solve complex problems? If so, joining our Professional Services team at Nutanix means becoming part of a dynamic organization recognized for its commitment to delivering exceptional solutions, where you’ll collaborate with talented professionals to advance groundbreaking technologies and make a tangible impact on client success. About The Team The Nutanix Professional Services team delivers a strong influence on the success of each Nutanix implementation by its customers. The Services function ensures success by engaging with customers in the pre-sales and post-sales stages by assisting in their software-defined data center (SDDC) strategy and architecture. Besides helping customers implement Nutanix products successfully, the Professional Services team, working with our partners, ensures customer success in fully implementing their virtualized and software-defined data centers. The Nutanix Professional Services Consulting function includes assessment, design, implementation, integration, and automation services as well as project management. Your Role • Design and implement scalable AI/Kubernetes infrastructure solutions on Nutanix HCI platforms, tailored to customer requirements. • Advise clients on best practices for configuring Kubernetes to efficiently manage AI/Kubernetes workloads. • Collaborate with cross-functional teams to align infrastructure capabilities with client AI/Kubernetes initiatives and strategies. • Develop and maintain documentation for solution configurations, deployment guides, and knowledge-sharing resources. • Monitor and optimize infrastructure performance, ensuring high availability and resource efficiency for AI model execution. • Act as a subject matter expert, providing guidance on GPU acceleration technologies and their integration in AI workflows. • Engage with clients to troubleshoot issues and provide ongoing support for their AI/Kubernetes infrastructures. • Achieve measurable improvements in client satisfaction and project outcomes within the first year, evidenced by successful deployments and positive feedback. What You Will Bring • Bachelor's degree in Computer Science, Information Technology, or a related field. • 5+ years of experience in designing and implementing infrastructure for data-intensive Kubernetes workloads. • Design, implement, and upstream new capabilities for Kubernetes and CNCF projects. • Strong expertise in container orchestration with Kubernetes. • Proficiency in networking concepts and architecture for implementing Kubernetes/AI workload • Proficiency with Git and GitHub workflows • Knowledge of various security compliance and cybersecurity requirements for Kubernetes/AI workloads. • Knowledge of DevOps cycle automation and implementation. • Knowledge of deployment lifecycle and resource requirements for AI/Kubernetes models, including LLM inference. • Proficiency in Infrastructure as Code (IaC) tools like Terraform or Ansible. • Experience with GPU acceleration technologies (e.g., NVIDIA CUDA) in containerized environments. • Familiarity with monitoring tools such as Prometheus and Grafana. • Exceptional communication and problem-solving skills with a client-focused mindset. • Excellent client-facing communication, presentation, and collaboration skills. • Strong problem-solving, analytical, and troubleshooting abilities. • Proven ability to work independently in a dynamic, customer-facing environment. • Experience with Hyperconverged Infrastructure (HCI) platforms is a strong plus. Work Arrangement Hybrid: This role operates in a hybrid capacity, blending the benefits of remote work with the advantages of in-person collaboration. In locations where our workplace policy applies (i.e. San Jose, Durham, Mexico City, Bangalore, Pune, Hoofddorp, Belgrade, Barcelona, Singapore, Sydney and Tokyo), employees are expected to work onsite a minimum of 3 days per week to foster collaboration, team alignment, and access to in-office resources. Workplace type may vary based on location and team requirements. Show more Show less

Bachelor's degree in Computer Science, Information Technology, or a related field. 5+ years of experience in designing and implementing infrastructure for data-intensive Kubernetes workloads. Design, implement, and upstream new capabilities for Kubernetes and CNCF projects. Strong expertise in container orchestration with Kubernetes. Proficiency in networking concepts and architecture for implementing Kubernetes/AI workload. Proficiency with Git and GitHub workflows. Knowledge of various security compliance and cybersecurity requirements for Kubernetes/AI workloads. Knowledge of DevOps cycle automation and implementation. Knowledge of deployment lifecycle and resource requirements for AI/Kubernetes models, including LLM inference. Proficiency in Infrastructure as Code (IaC) tools like Terraform or Ansible. Experience with GPU acceleration technologies (e.g., NVIDIA CUDA) in containerized environments. Familiarity with monitoring tools such as Prometheus and Grafana. Exceptional communication and problem-solving skills with a client-focused mindset. Excellent client-facing communication, presentation, and collaboration skills. Strong problem-solving, analytical, and troubleshooting abilities. Proven ability to work independently in a dynamic, customer-facing environment. Experience with Hyperconverged Infrastructure (HCI) platforms is a strong plus.

Design and implement scalable AI/Kubernetes infrastructure solutions on Nutanix HCI platforms, tailored to customer requirements. Advise clients on best practices for configuring Kubernetes to efficiently manage AI/Kubernetes workloads. Collaborate with cross-functional teams to align infrastructure capabilities with client AI/Kubernetes initiatives and strategies. Develop and maintain documentation for solution configurations, deployment guides, and knowledge-sharing resources. Monitor and optimize infrastructure performance, ensuring high availability and resource efficiency for AI model execution. Act as a subject matter expert, providing guidance on GPU acceleration technologies and their integration in AI workflows. Engage with clients to troubleshoot issues and provide ongoing support for their AI/Kubernetes infrastructures. Achieve measurable improvements in client satisfaction and project outcomes within the first year, evidenced by successful deployments and positive feedback.