Senior Technical Support Engineer

Who we are

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, such as developing new medicines, securing our financial markets, or protecting our country.

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. In the world of AI today, we believe that the future is still being invented — and we want to be the ones building it. For more information, visit

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, and 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 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: 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 all of you that believe improving is always possible. 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

Originally posted on Himalayas