Senior Technical Support Engineer - Domino Data Lab

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 — use our software to solve critical global challenges.

What We Are Building

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, ensuring every customer gets a clear and timely resolution. You'll also contribute to the knowledge base that helps the whole team scale.

What Your Impact Will Be

• 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 the EMEA weekend on-call rotation per team schedule.

What We Look For in This Role

• 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 expertise: 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: form a hypothesis, test it, and adapt when logs disagree with your theory.
• Clear written communicator: case updates and KB articles don't require follow-ups to understand.
• Comfortable managing multiple open, time-sensitive cases without losing track of details.
• 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

• Diversity: We strongly believe in growing a diverse team and encourage people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply.
• Growth Mindset: Creative individuals who dig into problems and see opportunities for success.
• Authenticity & Truth: Individuals who seek truth, speak truth, and bring their whole selves to work.
• Continuous Improvement: A shared belief that everything is a work in progress and can always be improved.
• Learning Environment: A focus on teaching and learning to equip employees with the tools needed for long-term success.