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Senior Technical Support Engineer - Domino Data Lab

Remote-firstFull-timeSeniorUTC+0–+3AsyncGermany#Python#Kubernetes#linux

About Domino Data Lab

At Domino, we build solutions that help the largest, highly regulated organizations adopt AI to accelerate mission-critical use cases. Our platform integrates a streamlined model and app development environment, advanced model, agent, and app hosting capabilities, and novel governance capabilities providing regulator-ready AI at scale. Our customers — like Johnson & Johnson, GSK, Bristol Myers, UBS, FINRA, and the US Navy — are using our software to solve some of the most important challenges in the world.

Backed by Sequoia Capital, Coatue Management, NVIDIA, Snowflake, and other leading investors, we have been in business for over a decade but are still a small team operating with the spirit of a startup.

What You'll Do

As a Technical Support Engineer, you're the bridge between our customers and our Engineering organization. You'll own technical support cases end-to-end, triaging issues across Kubernetes infrastructure, ML platform components, authentication, data connectivity, and model deployment, and ensuring every customer gets a clear and timely resolution.

  • Own support cases for enterprise customers across all severity levels, from initial triage through resolution, with clear communication and accurate expectations throughout.
  • Diagnose and resolve Kubernetes and cloud infrastructure issues: pod failures, resource limits, persistent volumes, RBAC, ingress, and cluster-level diagnostics.
  • Troubleshoot ML platform problems including workspace and job failures, environment build errors, model deployment issues, and data connector failures.
  • File detailed, actionable bug reports and enhancement requests in Jira and act as the customer's advocate with Product and Engineering.
  • Write and review knowledge base articles, how-to guides, and troubleshooting docs, building the reference layer that helps customers and teammates solve problems faster.
  • Hand off cases cleanly in a follow-the-sun model across AMER, EMEA, and APAC, ensuring continuity for global enterprise accounts.
  • Run live troubleshooting sessions with customers via video call and participate in EMEA weekend on-call rotation per team schedule.

What We Look For

  • 3 to 5 years in enterprise technical support, solutions engineering, or a similar customer-facing technical role at a SaaS or data/AI platform company.
  • Hands-on Kubernetes experience: pod lifecycle, kubectl, RBAC, namespaces, persistent volumes, and cluster-level troubleshooting.
  • Strong Linux and command-line proficiency: log analysis, process management, file system navigation, and shell scripting.
  • Familiarity with Python-based ML workflows: Jupyter, package management, model training and serving.
  • Experience with cloud platforms (AWS, GCP, or Azure) and containerized application environments.
  • Methodical troubleshooter: you form a hypothesis, test it, and adapt when the logs disagree with your theory.
  • Clear written communicator: your case updates and KB articles don't require a follow-up to understand.
  • Comfortable managing multiple open, time-sensitive cases without losing the thread on any of them.
  • Works well asynchronously across time zones in a remote-first, globally distributed team.
  • Bachelor's degree in computer science, engineering, or a related technical field (or equivalent experience).

What We Value

  • We strongly believe in the value of growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply.
  • We value a growth mindset: high-performing creative individuals who dig into problems and see the opportunities for success.
  • We believe in individuals who seek truth and speak the truth and can be their whole selves at work.
  • We value continuous improvement. At Domino, everything is a work in progress – we can do better at everything.
  • We emphasize an environment of teaching and learning to equip employees with the tools needed to be successful in their function and the company.

Timezone overlap

UTC+0–+3

Culture

Async-friendly

Open to

Germany

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