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Open nowPosted today

Pre-Sales Engineer

MyCareersFuture94,028 open roles

Pay
SGD 3,000 – SGD 5,000 a month
Where
West, Singapore
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Your applicationOpen nowPre-Sales EngineerMyCareersFuture · West, Singapore

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This job: posted today

The posting

Job Description

We are looking for an AI Infrastructure Solutions Architect (Pre-Sales) to join QuettaFlow Technologies Pte Ltd. The role focuses on developing end-to-end AI infrastructure solutions covering GPU computing, servers, networking, data centre infrastructure and liquid cooling.

The successful candidate will work closely with customers, sales and engineering teams to understand technical requirements, design suitable solutions, support proof-of-concept (POC) activities and prepare technical proposals.

Key Responsibilities

  1. Engage with customers, including enterprises, AI companies, data centre operators and technology teams, to understand their AI infrastructure and computing requirements.
  2. Design and propose end-to-end AI infrastructure solutions covering: GPU / AI servers GPU clusters and HPC infrastructure Storage and data centre networking InfiniBand / RoCE networking Power and cooling requirements Liquid cooling / immersion cooling solutions
  3. Perform GPU and compute capacity planning, including GPU selection, VRAM requirements, server configuration, network bandwidth and infrastructure sizing.
  4. Understand AI workloads, including large language models (LLMs), AI inference and training, and translate business requirements into practical hardware and infrastructure solutions.
  5. Support AI infrastructure POCs, technical demonstrations, customer presentations and solution validation.
  6. Prepare technical proposals, solution documents, architecture diagrams, presentations, technical specifications and tender / quotation responses.
  7. Work closely with sales, engineering, suppliers and project delivery teams to ensure proposed solutions are technically feasible and deliverable.
  8. Conduct technical discussions with customers' CTOs, IT infrastructure, data centre, network and AI / engineering teams.
  9. Monitor industry developments, emerging GPU technologies, AI infrastructure solutions and competitor offerings, and contribute to the development of solution templates and technical materials.
  10. Identify technical risks and provide appropriate solutions during the pre-sales and project planning stages.

Requirements

  1. Bachelor's degree or above in Computer Science, Computer Engineering, Information Technology, Telecommunications, Networking, Mechanical Engineering, HVAC / Building Services Engineering, or a related discipline.
  2. 3–6 years of experience in IT pre-sales, solutions architecture, technical consulting, data centre infrastructure, HVAC / cooling systems, or related fields, with relevant experience in AI computing, GPU infrastructure, data centres or related projects.
  3. Strong knowledge of x86 / AI servers, GPU / NPU, storage and computing clusters, including server selection and computing capacity assessment.
  4. Good understanding of data centre networking, InfiniBand (IB), RoCE, switches and GPU cluster networking.
  5. Practical understanding of LLM training and inference, private AI deployment, RAG and AI infrastructure requirements.
  6. Knowledge or experience in data centre cooling, HVAC, liquid cooling or immersion cooling systems will be an advantage.
  7. Proficient in preparing technical solutions, PowerPoint presentations, architecture diagrams and technical tender responses.
  8. Familiar with Linux fundamentals, containers and Kubernetes. Knowledge of AI computing resource scheduling is an advantage.
  9. Strong communication, presentation and customer-facing skills.
  10. Good written and spoken English. Knowledge of Mandarin will be an advantage.

Added Advantage

  • Experience with AI / GPU data centres, HPC or large-scale GPU clusters.
  • Experience with liquid cooling, immersion cooling or other advanced data centre cooling technologies.
  • Experience with NVIDIA GPU platforms, InfiniBand or RoCE networking.
  • Experience in AI infrastructure system integration or data centre projects.
  • Experience supporting POCs or large enterprise / government technology projects.
  • Knowledge of Kubernetes, Docker or AI cluster management / scheduling.
  • Experience with technical tenders and government / enterprise projects.
  • Good command of written and spoken English.

What We Offer

  • Opportunity to work on emerging AI infrastructure and GPU computing projects.
  • Exposure to AI compute, data centre infrastructure and advanced liquid cooling technologies.
  • Opportunity to work with customers, technology partners and engineering teams on end-to-end AI infrastructure solutions.
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