Customer Engineer, High Performance Computing, Google Cloud - Singapore

GOOGLE ASIA PACIFIC PTE. LTD.; Singapore; On-site; SGD 140,000 - 190,000; Full time

Job summary

Google Cloud APAC is seeking a Specialist Customer Engineer to accelerate customer success. You will partner with technical Sales teams as a subject matter expert in HPC and AI Infrastructure, helping customers design, turn up, and optimize large-scale AI workloads on Google Cloud TPU.

Excellent technical, communication, and organizational skills are essential. You will collaborate with product marketing and engineering, staying ahead of industry trends and crafting practical cloud solutions.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 6 years of cloud-native or HPC infrastructure architecture experience in a customer-facing role.
• Experience deploying distributed AI/ML workloads with frameworks (PyTorch, JAX) and schedulers (Kubernetes, Slurm).
• Experience with Linux, cluster control planes, and data center infrastructure integration.

Responsibilities

• Drive pre-sales technical strategy and build go-to-market solutions with customers and data center hosting partners to accelerate business cycles and land TPU deployments across APAC.
• Serve as a trusted technical advisor on end-to-end architecture and integration strategies across the TPU software stack and customer/partner environments.
• Guide customers and hosting partners through technical qualification, pod layout design, system turn-up, and operational readiness.
• Conduct workload profiling, migration, and optimization of large-scale training/inference models for Google Cloud TPU hardware topologies.

Skills

Cloud HPC architecture

Pre-sales / solutions architecture

Distributed AI/ML workloads

Linux & data center infra

Kubernetes

Slurm

PyTorch

JAX

Prometheus

Education

Bachelor's degree or equivalent

Tools

Prometheus

BMC/Redfish

Job description

Product area

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.

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.

Additional job description

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.

Qualifications

Job responsibilities

• 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).

Minimum qualifications

• Bachelor's degree or equivalent practical experience.
• 6 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).

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 client relationship management in this region.