Customer Engineer, AI, Infrastructure Modernization

Minimum Qualifications:

• Bachelor's degree or equivalent practical experience.
• 10 years of experience with cloud native architectures and modern cloud infrastructure (e.g., hardware shapes, sizes, auto-scaling, auto-provisioning, etc.) and with networking, switching/routing for ethernet/RoCE/infiniband in a customer-facing or support roles.
• Experience with high performance infrastructure technology, on-premise infrastructure engineering, virtualization, or containerization platforms and orchestrators such as Slurm, Kubernetes, for building and operationalizing AI Models training and inference.
• Experience engaging with, and presenting to, technical stakeholders and executive leaders

Preferred Qualifications:

• Master's degree in Computer Science, Mathematics, a related technical field.
• Experience as an IT infrastructure consultant or enterprise architect working in data center investment strategies and proposals.
• Experience with leveraging AI hardware and software stacks and platforms to bring up and deploy AI compute clusters.
• Experience with AI Infrastructure systems, networking technologies (e.g., DPU, RoCE, InfiniBand), cooling, and accelerators, GPUs and TPUs.
• Knowledge of the AI infrastructure market, including main technology providers, differentiators and trends.
• Ability to grow in fluid environments.

About The Job

When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products.

As part of an entrepreneurial team, you will play a key role in understanding the needs of our customers and help shape the future using AI technology. You will work with Google Cloud Platform (GCP's) technology and complete AI stack and position the same to our customers in all verticals.

As Customer Engineer, your experience and thought leadership will support Google Cloud sales teams to deploy Google Cloud’s industry leading AI/ML accelerators (TPU/GPU) at AI innovators, large enterprises, and early stage AI startups. You will help customers innovate faster with solutions using Google Cloud’s flexible and open AI infrastructure.

You will be working with Google customers on AI Infrastructure server and networking infrastructure deployments. Guide customer discussions on network topologies, compute/storage and support bring up of the server/network/cluster/cooling deployments. You will need to visit the customer data center during the bring up phase.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities

• Become trusted advisors to the customers, helping them understand and incorporate AI accelerators into their overall cloud and IT strategy by designing training and inferencing platforms, using the latest accelerators Google Cloud has to offer.
• Demonstrate how Google Cloud is differentiated, highlighting the power of accelerators by working with customers on Proof-of-Concepts, demonstrating features, optimizing model performance, profiling, and bench marking.
• Work with customers to demonstrate and prototype Google Cloud technology integrations in customer/partner environments, including customer/partner datacenters. Help the Account team to close agreements from a technical perspective.
• Influence Google Cloud strategy where infrastructure and AI/ML meet by advocating for enterprise customer requirements collaborating with AI Infra Dedicated Engineering Team.
• Travel to customer sites, conferences, datacenters, and other related events as needed.