Customer Solutions Engineer, Compute, Cloud
Posted 13 Nov 2026, 05:52 ET
This job at a glance
- Who can apply
- New grads, no experience needed · Bachelor's degree
- Must know
- LinuxNetworkingTroubleshootingSalesStakeholder managementPython
- Nice to have
- Machine learningSystem designPyTorchTensorFlow
- Work
- On-site in Kirkland
- Pay
- Not stated by the employer.
- Skill demand
- Sales24%Troubleshooting13%Networking1%of 146 similar entry-level jobs posted in the US this week
- Listed
- Nov 13, 2026 · still open
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About the Role
- Customer Solutions Engineers for AI Infrastructure manage complex customer issues and provide specialized support to other teams.
- This role is part of a global team providing 24x7 support to ensure customers can seamlessly deploy their AI and ML workloads on AI Infrastructure products.
- The position requires troubleshooting technical problems using a mix of hardware and software debugging, networking, Linux system administration, coding/scripting, and documentation updates.
- The role aims to improve the product, internal tools, processes, and documentation, and drive business growth by recognizing and advocating for customer challenges related to AI deployments.
- This role requires working in a shift pattern or non-standard work hours, which may include weekend work.
Responsibilities
- Manage customer problems through effective diagnosis, resolution, or implementation of new investigation tools to increase productivity for customer issues on AI/ML infrastructure.
- Develop an in-depth understanding of AI/ML workloads and underlying hardware architectures by troubleshooting, reproducing, determining the root cause for customer-reported issues, and building tools for faster diagnosis.
- Act as a consultant and subject matter expert for internal stakeholders in Engineering, Sales, and customer organizations to resolve complex deployment and operational obstacles in AI infrastructure environments.
- Work closely with multiple Product and Engineering teams to find ways to improve the product.
- Interact with Site Reliability Engineering (SRE) teams to drive high-quality production.
- Be available for non-standard work hours or shifts, which may include weekends as needed.
Requirements & Tech Stack
- Minimum Qualifications:
- Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
- Experience in reading/debugging code written in a general-purpose coding language (e.g., Java, C, C++, Python, Shell, Go or JavaScript, etc.).
- Experience with virtualization and orchestration frameworks.
- Experience troubleshooting and advocating for customer needs.
- Experience triaging technical issues across the stack (e.g., hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, performance).
- System administrator level experience with Linux/Unix systems.
- Experience in debugging issues across the hardware/software boundary on enterprise-grade server infrastructure.
- Preferred Qualifications:
- Experience working with large-scale distributed systems.
- Familiarity with common solutions, design patterns, or best practices.
- Experience working directly with AI/ML computing hardware, including GPUs or other accelerators.
- Experience with ML frameworks (e.g., TensorFlow, PyTorch).
- Understanding of the AI/ML training and inference lifecycle.
- Experience with containerization and orchestration technologies like Kubernetes or Slurm in an on-prem or cloud environment.
Compensation
- US: $102,000 - $144,000 (USD) + 15% bonus target + equity + benefits.