82 Harris Computer Systems Technical Support Engineer Jobs Hiring Near You

Our mission is simple: deliver seamless, secure, reliable, and resilient AI compute at scale. We've built a versatile cloud platform that eliminates infrastructure barriers, empowering builders to focus on innovation instead of fighting their stack. Because breakthrough AI should move at the speed of ideas, not infrastructure.

We are building our level 2 technical support team from the ground up, and we are looking for a Technical Support Engineer to join it.

Our customers are not filing tickets about forgotten passwords; they are AI companies running massive GPU training jobs and production inference at scale, and when they contact us, something real is wrong. A node is reporting 7 GPUs instead of 8. A training run that has been going for 4 days is suddenly crawling, and nobody can say why. A Slurm partition is draining, and the queue is backing up. Our global operations center catches and handles what the runbooks cover, around the clock, everything past that comes to you.

This is a hands‑on diagnostic role for someone who genuinely enjoys the hunt. You will work Linux systems at depth, live inside Kubernetes and Slurm, read logs and metrics until the story makes sense, and talk directly to customer engineers who are every bit as technical as you are. When you solve something new, you will write it down so the global operations center can solve it next time without you.

Because the tier is new, you will help define it: the escalation paths, the runbooks, the diagnostic tooling, the standards. If you have ever looked at a support organization and thought I could build this properly if someone would let me, this is that opening:

Reporting to the technical support manager within customer experience.

• Own level 2 tickets escalated from the global operations center, driving them to resolution or to a clean, well‑evidenced handoff to engineering.
• Diagnose issues across the full stack, Linux hosts, GPU health, Kubernetes workloads, Slurm scheduling, Weka and Vast storage, and high‑speed networking.
• Investigate degraded and failed training and inference workloads using logs, metrics, and cluster telemetry, and give customers a clear account of what happened and why.
• Triage GPU and node hardware faults, including nodes presenting fewer than 8 GPUs, RMA candidates, and thermal or power events, and coordinate with data center operations on remediation.
• Work directly with customer engineering teams in writing and on calls, matching their technical level and keeping them informed while an investigation is open.
• Write and maintain runbooks that let the global operations center resolve recurring issues at level 1 and flag the gaps where no runbook exists yet.
• Build diagnostic scripts and small tools that shorten investigations and reduce repeat work.
• Contribute to the customer‑facing knowledge base and documentation, so recurring questions stop becoming tickets.
• Partner with technical account managers on account health, giving them the technical read behind utilization dips and ticket trends.
• Participate in an on‑call rotation backing the global operations center outside business hours and help shape the teams move toward full 24‑7 coverage.
• Feed repeated patterns back to engineering and product as evidence, not anecdote.

• 3+ years in Linux systems administration, site reliability engineering, infrastructure operations, or a technical support engineering role with real diagnostic ownership.
• Strong Linux troubleshooting depth: system, networking, file systems, storage, process and resource investigation, log analysis, and comfort at the kernel boundary when applications go quiet.
• Working knowledge of Kubernetes, reading cluster and pod state, understanding scheduling and placement, and diagnosing why a workload will not run.
• Experience with a batch scheduler in a shared compute environment, ideally Slurm, including job submission, queue behavior, and node state
• Scripting ability in Python or Bash, sufficient to automate diagnosis
• Experience working tickets in a structured incident and tracking system such as JIRA, PagerDuty, or equivalent.
• Excellent written communication, specifically the ability to explain a technical finding clearly to an engineer who is frustrated and under time pressure,
• Willingness to participate in an on‑call rotation.

• Background in GPU cloud, HPC, or AI/ML infrastructure operations.
• Familiarity with AMD Instinct platforms, MI300X, MI325X, MI355X, and the ROCm software ecosystem, or transferable depth with NVIDIA/CUDA,
• Experience diagnosing high‑speed networking issues, RDMA, link performance, and the class of problems where the GPUs look healthy but throughput has collapsed.
• Exposure to Weka, Vast, or other high‑performance storage environments.
• Container runtimes in HPC contexts, Docker, Enroot, Pixis, or Aptainer
• Hands‑on use of observability platforms such as Grafana and Prometheus
• Understanding of distributed training frameworks, PyTorch, JAX, and inference‑serving patterns, enough to recognize when a failure is the customer’s code rather than our infrastructure.
• Experience with ITIL, or another structured incident and change management framework.

• Stock Options

• 100% paid Medical, Dental, and Vision insurance for Employees

• Company Health Savings Account Contributions

• 100% paid Short Term and Long Term Disability Insurance for Employees

• Life and Voluntary Supplemental Insurance Options

• Other Insurance Options, such as Pet & Legal Insurance

• Various Supplementary Health Benefits, such as discounted Virtual Healthcare Appointments and Serious Illness Support

• Flexible Spending Account

• 401(k)

• Employee Assistance Program

• Flexible PTO

• Paid Holidays

• Parental Leave

• Other In-Office Perks

TensorWave is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of any protected status under applicable law.

TensorWave provides reasonable accommodations in accordance with applicable laws. If you require accommodation during the hiring process, please contact accomodations@tensorwave.com.

All offers of employment are contingent upon verification of identity and authorization to work in the United States, as required by law.

Where permitted by law, employment may be contingent upon the successful completion of a job‑related background check.

By submitting an application, you acknowledge that TensorWave may collect, use, and retain your personal information for recruiting and employment-related purposes in accordance with applicable data privacy laws.