Customer Engineer, High Performance Computing (English)

Google LLC; Singapore; On-site; SGD 180,000 - 280,000; Full time

Job summary

Google Cloud seeks a Specialist Customer Engineer with deep HPC expertise to accelerate customer success. You will partner with technical sales teams to differentiate Google Cloud, develop cloud architectures for large-scale AI/ML workloads, and lead proofs of concept.

Your role includes troubleshooting complex questions and presenting practical, scalable solutions to customers and partners. You will collaborate with product marketing and engineering teams to stay ahead of industry trends, while

Qualifications

• Bachelor's degree or equivalent practical experience required.
• 10 years of experience with cloud-native or HPC infrastructure architectures in a customer-facing pre-sales or deployment role.
• Experience developing and orchestrating distributed AI/ML workloads using PyTorch, JAX, vLLM, or SGLang and schedulers like Kubernetes or Slurm.
• Experience with Linux host software, cluster control planes, and data center integration.
• Fluent English communication to collaborate with regional customers and global teams.

Responsibilities

• Partner with technical sales teams as a subject matter expert in HPC to differentiate Google Cloud offerings.
• Develop creative cloud solutions and architectures to address business challenges.
• Engage in proofs of concepts and troubleshoot technical questions and roadblocks.
• Present practical solutions to customers and partners, supported by strong presentation and communication skills.
• Collaborate with product marketing, engineering, and data center partners to stay ahead of industry trends.

Skills

High Performance Computing

Cloud architecture

Pre-sales

Distributed AI/ML workloads

Kubernetes

Slurm

Linux

English fluency

Mandarin fluency

PyTorch

Education

Bachelor's degree or equivalent practical experience

Tools

Prometheus telemetry pipelines

Redfish API

Pallas profiler

XProf

Job description

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.

Specialist Customer Engineers seek to accelerate Google Cloud customer success by providing domain-specific technical expertise, while responsibly influencing products and solutions.

In this role. you will partner with technical Sales teams as a subject matter expert in High Performance Computing (HPC) to differentiate Google Cloud to the customers. You will help prospective and existing customers and partners understand the power of Google Cloud, develop creative cloud solutions and architectures to solve their business challenges, engage in proofs of concepts, and troubleshoot any technical questions and roadblocks. You will use your expertise and presentation skills to engage with customers to understand their business and technical requirements, and present practical and useful solutions on Google Cloud. You will have excellent technical, communication and organizational skills.

You will be a part of a team of fellow Googlers working in an environment of respect where we promote equal opportunities to succeed.

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.

Minimum qualifications:

- Bachelor's degree or equivalent practical experience.

- 10 years of experience with cloud-native or high-performance computing (HPC) infrastructure architecture in a customer-facing pre-sales, solutions architecture, or deployment engineering role.

- Experience developing, deploying, and orchestrating distributed AI/ML workloads using modern frameworks (e.g., PyTorch, JAX, vLLM, or SGLang) and job schedulers (e.g., Kubernetes or Slurm) on AI accelerator hardware.

- Experience with Linux host software, cluster control planes, and data center infrastructure integration (compute, high-speed networking, and storage).

- Ability to communicate in English fluently to collaborate with regional customers, data center partners, and global engineering teams.

Preferred qualifications:

- Experience integrating large-scale accelerator clusters with customer and data center partner software stacks, including fleet management APIs, IaaS operations tools, out-of-band hardware management (BMC/Redfish), and Prometheus telemetry pipelines.

- Experience designing, turning up, and operating large-scale AI/HPC infrastructure farms, including data center space, power, liquid cooling (CDU), Optical Circuit Switches (OCS), Top-of-Rack (ToR) networking, and hardware RMA/repair playbooks.

- Experience with lower-level performance profiling and kernel optimization tools (e.g., XProf, PyTorch Profiler, Pallas, or MaxText) to diagnose and resolve distributed training and inference bottlenecks.

- Ability to communicate in Mandarin fluently to support customers in the region.

- Drive pre-sales technical strategy and build go-to-market solutions with customers and data center hosting partners to accelerate business cycles, resolve technical objections, and land large-scale Google Cloud TPU agreements and deployments across APAC.

- Serve as a trusted technical advisor on end-to-end architecture and integration strategies across the TPU software stack and customer or partner environments (fleet management systems, job schedulers, IaaS operations tooling, ancillary storage/compute, and data center networking/WAN).

- Guide customers and hosting partners through technical qualification, pod layout design, system turn-up, and operational readiness—covering slice lifecycle management, OS and firmware upgrades, telemetry integration, and hardware maintenance workflows.

- Conduct workload performance profiling, workload migration, and optimization of large-scale training and inference models and data pipelines specifically for Google Cloud TPU hardware topologies (e.g., 3D Torus over Inter-Chip Interconnect and Optical Circuit Switches).