Technical Support Engineer (Inference) - US Weekends

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 GPU clusters and our inference and fine-tuning services; ensure swift and effective solutions every time.
• Act as a customer facing SRE to ensure our customer’s Inference endpoints (running on Kubernetes) remain healthy, stable, and performant
• Become a product expert in all of our Gen AI solutions, serving as the last line of technical defense before issues are escalated to Engineering and Product teams.
• Assist with hardware and platform migrations by validating system health and traffic routing. Monitor dashboards to detect anomalies and escalate with data-backed analysis
• Manage customer-facing communications during incidents and degradations; translate deep technical findings (latency regressions, provider issues, network reachability drops) into clear, evidence-backed updates without exposing platform internals
• Contribute infrastructure changes for model deployment, capacity rebalancing, and cluster configuration. You will execute infrastructure changes via pull requests (infra-as-code) for tasks such as endpoint configuration, model bringup/bringdown, and capacity scaling
• Flag engine-level bugs with log