Senior Technical Support Engineer

Posted Yesterday
Be an Early Applicant
Hiring Remotely in United Kingdom
Remote or Hybrid
Senior level
Artificial Intelligence • Machine Learning
Unleash data science, one innovation at a time.
The Role

Who we are

At Domino, we build software that helps the largest, AI-driven organizations build and operate advanced data science and AI solutions at scale. Our platform integrates a streamlined model development environment, MLOps capabilities, and novel features for collaboration, reuse, and reproducibility — all of which make data science teams more productive, reduce time to value, and ensure compliance. 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 a decade but are still a small team operating with the spirit of a startup. Especially 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 www.domino.ai

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

#LI-Remote

Skills Required

  • 3 to 5 years of experience 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, including pod lifecycle, kubectl, RBAC, namespaces, persistent volumes, and cluster-level troubleshooting
  • Strong Linux and command-line proficiency, including log analysis, process management, file system navigation, and shell scripting
  • Familiarity with Python-based ML workflows, including Jupyter, package management, model training, and model serving
  • Experience with AWS, GCP, or Azure and containerized application environments
  • Methodical troubleshooting and hypothesis-driven problem solving
  • Clear written communication for customer case updates and knowledge-base articles
  • Ability to manage multiple open, time-sensitive cases
  • Ability to work 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

Domino Data Lab Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Domino Data Lab and has not been reviewed or approved by Domino Data Lab.

  • Healthcare Strength Health coverage is positioned as premium, including a $0‑premium option for employees and dependents, with mental‑health coverage and a Calm subscription available. These features point to robust medical, dental, and vision support.
  • Leave & Time Off Breadth Time off and flexibility are emphasized through flexible/unlimited PTO and a remote‑first approach. This setup signals considerable autonomy in managing time away from work.
  • Wellbeing & Lifestyle Benefits Extras such as commuter benefits, a home‑office/equipment stipend, and wellness reimbursements expand everyday support. An EAP and fitness perks further bolster lifestyle and wellbeing offerings.

Domino Data Lab Insights

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The Company
HQ: San Francisco, CA
200 Employees
Year Founded: 2013

What We Do

Domino Data Lab powers model-driven businesses with its leading Enterprise AI platform trusted by over 20% of the Fortune 100. Domino accelerates the development and deployment of data science work while increasing collaboration and governance. With Domino, enterprises worldwide can develop better medicines, grow more productive crops, build better cars, and much more. Founded in 2013, Domino is backed by Coatue Management, Great Hill Partners, Highland Capital, Sequoia Capital and other leading investors. For more information, visit www.domino.ai

Why Work With Us

We’re looking for sharp, scrappy people who crave a high degree of ownership, are laser-focused on personal growth, and can stick the landing between high standards and low ego. In our fast-paced environment, you’ll find all the white space and opportunity you need to thrive.

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