About the job
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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 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 Professional Services team delivers a strong influence on the success of each 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 products successfully, the Professional Services team, working with partners, ensures customer success in fully implementing their virtualized and software-defined data centers. The Consulting function includes assessment, design, implementation, integration, automation services as well as project management.
Your Role
- Design and implement scalable AI/Kubernetes infrastructure solutions on 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 workloads.
- 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.
