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Technical Support Engineer (GPU Clusters) - US Weekends

Join Together AI as a Technical Support Engineer to tackle complex challenges in GPU clusters while supporting customer success.

Location
Remote
Compensation
$160k–$230k/yr
Level
mid
Type
full time

Posted by employer 2 months ago

First seen on Joblaze 2 months ago

Last verified on the company career page 7 hours ago

Requirements

Experience
3+ years

Not disclosed in this posting: work arrangement, visa sponsorship.

Benefits

Equity/Stock Options Remote Work Health Insurance

Joblaze summary

In the role of Technical Support Engineer at Together AI, the individual will engage with customers to resolve intricate technical issues related to Kubernetes GPU clusters, ensuring optimal performance and stability. Key skills include a strong background in AI technologies, Kubernetes, and high-performance computing, along with experience in customer-facing technical support. This position is ideal for someone with several years of experience in a similar role, particularly those with a passion for AI and a proactive approach to problem-solving. Together AI fosters a collaborative environment, working closely with various teams to enhance customer satisfaction and drive product improvement

Joblaze insights

  • Listed about 2 months ago — first seen on Joblaze August 5, 2026. Last confirmed on Together AI's careers page October 24, 2026.
  • Salary band is in line with the typical range for DevOps/SRE roles (median ~$165,000).
  • Starts above 78% of 50 comparable mid devops/sre roles in United States that list Kubernetes we track (median $125,000 across 18 companies). See Kubernetes salary trends
  • Kubernetes appears in 60.7% of 122 comparable mid devops/sre roles in United States; ML appears in 0.8% of 122 comparable mid devops/sre roles in United States.

Quick facts

What's the salary range?
Together AI lists $160,000–$230,000 for this role.
How much experience is required?
At least 3 years of relevant experience for this Technical Support Engineer (GPU Clusters) - US Weekends role.
What's the tech stack?
Joblaze extracted these technologies from the posting: AI, Ansible, GPU, HPC, Infiniband, Kubernetes.
What seniority level is this role?
Together AI targets mid-level candidates for this position.
Is this full-time or contract?
Full-time for this Technical Support Engineer (GPU Clusters) - US Weekends role at Together AI.

From the original posting

About the role

As a Technical Support Engineer at a pioneering AI company, you'll be the first line of defense to support customers as they build out training, fine tuning, and inference solutions with Together AI. You'll dive deep into complex technical challenges, providing swift and effective solutions while serving as a product expert. As a part of the Customer Experience organization, you will collaborate closely with product and sales, driving continuous improvement of our offerings. This is an exciting opportunity for a deeply technical professional passionate about AI and customer success to make a significant impact in a fast-paced, innovative environment.

Required hours

  • This is a fulltime position working US daytime hours. The role will work both weekend days (Saturday and Sunday) as well as two additional weekdays.
  • This is a 4-day shift, 10 hours per day, with 2 additional hours of on-call coverage on Saturdays and Sundays.
  • The role would start as a Monday to Friday role for the first few months to allow for ramping up and learning from teammates. After being considered fully ramped, the role would transition to the 4-day weekend shift.

Responsibilities

  • Engage directly with customers to tackle and resolve complex technical challenges involving our cutting-edge Kubernetes GPU clusters; ensure swift and effective solutions every time.
  • Act as a customer facing SRE to ensure our customer’s Kubernetes clusters remain healthy and stable
  • Become a product expert in our GPU Cluster service, serving as the last line of technical defense before issues are escalated to Engineering and Product teams.
  • Monitor GPU cluster health and proactively communicate hardware issues to customers (thermal throttling, BMC failures, missing GPUs, and NVLink/InfiniBand degradation) with clear remediation steps
  • Operate and maintain production infrastructure for enterprise GPU customers, including fleet rebalancing, Slurm cluster maintenance, node repair/migration, and Kubernetes-based workload management
  • Investigate and resolve storage and networking issues such as Weka filesystem degradation, InfiniBand link failures, and bandwidth anomalies on bare-metal and VM environments
  • Collaborate seamlessly across Engineering, Research, and Product teams to address customer concerns; collaborate with senior leaders both internally and externally to ensure the highest levels of customer satisfaction.
  • Transform customer insights into action by identifying patterns in support cases and working with Engineering and Go-To-Market teams to drive Together’s roadmap (e.g., future models to support)
  • Maintain detailed documentation of system configurations, procedures, troubleshooting guides, and FAQs to facilitate knowledge sharing with team and customers.
  • Be flexible in providing support coverage during holidays, nights and weekends as required by business needs to ensure consistent and reliable service for our customers.

Requirements

  • 3+ years of experience in a customer-facing technical role with at least 1 year in a support function for an AI service or supporting a mission-critical API in SaaS
  • Experience as an SRE or DevOps engineer working with Kubernetes
  • Strong technical background, with knowledge of AI, ML, GPU technologies and their integration into high-performance computing (HPC) environments.
  • Advanced knowledge with infrastructure services (e.g., Kubernetes, SLURM), infrastructure as code solutions (e.g., Ansible) high-performance network fabrics, NFS-based storage management, container infrastructure, and scripting and programming languages.
  • Experience with HPC/Slurm cluster environments — node draining, job scheduling, maintenance workflows
  • Familiarity with high-speed networking concepts — InfiniBand, RDMA, network interface diagnostics
  • Experience with distributed storage systems (e.g., Weka, NFS) and troubleshooting I/O and bandwidth issues
  • Foundational understanding in the installation, configuration, administration, troubleshooting, and securing of compute clusters.
  • Complex technical problem solving and troubleshooting, with a proactive approach to issue resolution
  • Ability to work cross-functionally with teams such as Sales, Engineering, Support, Product and Research to drive customer success.
  • Strong sense of ownership and willingness to learn new skills to ensure both team and customer success.
  • Excellent communication and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders.
  • Ability to operate in dynamic environments, adept at managing multiple projects, and comfortable with frequent context switching and prioritization.

Compensation

We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $160K - $230K + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

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