---
title: 'Senior Technical Support Engineer at Domino Data Lab'
canonical: 'https://feeny.ai/job/senior-technical-support-engineer-domino-data-lab-germany-yfvfjhqwgajk'
type: 'job'
last_seen: '2026-09-09'
---

# Senior Technical Support Engineer at Domino Data Lab

- **Company:** Domino Data Lab
- **Location:** Germany
- **Work type:** remote
- **Posted:** 2026-09-02
- **Last confirmed live:** 2026-09-09
- **Apply:** https://app.careerpuck.com/job-board/domino-data-lab/job/8174953?gh_jid=8174953

## Job description

## 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

## About Domino Data Lab

## Company Overview
- **One-liner**: Domino Data Lab provides an enterprise AI platform that unifies tools, infrastructure, and governance to help organizations build, scale, and govern AI-powered applications.
- **Entity Type**: Private (Series F)
- **Headquarters**: San Francisco, California, USA
- **Founded**: 2013
- **Founders**: Nick Elprin (CEO), Christopher Yang, and Matthew Granade

## Core Business
- **Primary industry**: Enterprise AI / MLOps / Data Science and Machine Learning Platforms
- **Target customers**: B2B, highly regulated enterprises — including 20% of the Fortune 100, such as life sciences, financial services, insurance, and public sector organizations.
- **Mission**: "Unleash AI to address the world’s most important challenges" — helping enterprises accelerate science and research while reducing cost, risk, and complexity.

## Products & Services
- **[Model Factory]**: The core development environment for building AI systems and applications. Supports every method from statistical computing to agentic AI, with any coding assistant, language, or framework. [domino.ai](https://domino.ai/)
- **[Governance Center]**: Govern AI systems and applications to reduce risk and ensure compliance. Defines policies once and enforces them across the entire lifecycle with complete auditability, quality control, and cost visibility. [domino.ai](https://domino.ai/)
- **[App Hub]**: Scale AI-powered applications to thousands of users securely. Delivers governed applications to decision-makers with no rewrites from development to production. [domino.ai](https://domino.ai/)
- **[Agentic AI]**: Design autonomous agents with any framework, deploy them as governed applications, and manage them across their entire lifecycle — all in one platform. [domino.ai](https://domino.ai/)
- **[Coding Assistants]**: Adds traceability, reproducibility, and governance to everything produced by coding assistants. [domino.ai](https://domino.ai/)
- **[Model Risk Management (MRM)]**: A platform for the full model lifecycle, from development through ongoing regulatory compliance, enabling faster model validation with fewer audit findings. [domino.ai](https://domino.ai/)
- **[Document Intelligence]**: Build AI that reads, classifies, and extracts insight from documents at scale, enabling faster decisions from unstructured data at lower cost. [domino.ai](https://domino.ai/)
- **[Statistical Computing Environments (SCE) Solutions]**: A fully reproducible, audit-ready platform for SAS, R, and Python, designed for faster clinical trial submissions with lower compliance risk. [domino.ai](https://domino.ai/)

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed.
- **Key Metric**: Total Funding — Over $300 million raised (backed by notable investors). The platform is trusted by over 20% of the Fortune 100. [domino.ai](https://domino.ai/company)
- **Notable Investors/Partners**: Coatue Management, Great Hill Partners, Highland Capital, Sequoia Capital, and other leading investors. [builtin.com](https://builtin.com/company/domino-data-lab)
- **Growth Signals**: Named to Inc.’s 2026 Best Workplaces list. Recognized in the 2025 Gartner Magic Quadrant for Data Science and Machine Learning Platforms. Customer wins include the U.S. Navy (75% reduction in model deployment time), Moody's (50%+ reduction in deployment time), and UBS (5-year partnership for model risk management). [domino.ai](https://domino.ai/)

## Competitive Advantages
- **End-to-end, unified platform**: Combines development (Model Factory), governance (Governance Center), and deployment (App Hub) into a single platform — a holistic approach that reduces cost, risk, and complexity.
- **Built for highly regulated enterprises**: Domino's governance-by-default design is purpose-built for industries like finance, life sciences, and defense, where compliance and auditability are non-negotiable.
- **Proven impact at scale**: Customers report a 6x reduction in infrastructure costs, a 50% reduction in end-to-end model lifecycle time, 40% faster model development, and 75% faster model deployment. [domino.ai](https://domino.ai/)
- **Reproducibility by default**: Every experiment, model, and decision is captured automatically, allowing teams to reproduce any result without manual reconstruction — a critical moat in regulated environments.

## Strategic Focus
- **Agentic AI and AI-powered applications**: Domino is heavily investing in enabling agentic AI workflows and the deployment of AI-powered applications at scale, as evidenced by their new "Agentic AI" and "App Hub" product lines.
- **Deepening governance and compliance**: The "Governance Center" and "Model Risk Management" solutions indicate a strategic focus on making compliance a core feature, not an afterthought, for enterprise AI.
- **Industry-specific solutions**: Targeting specific verticals like life sciences (SCE solutions), financial services (MRM), and defense (U.S. Navy collaboration) to create tailored, high-value offerings.

## Why Work Here
- **Impact-driven mission**: Employees work on solving "the world’s most important problems" — from developing new medicines and more efficient crops to building safer defense systems.
- **Flexible work environment**: Domino operates a hybrid workspace with "flexible" on-site time. They have offices in San Francisco, London, and a remote hub in Argentina. The company states: "Feel supported to get your work done how and when you need to, regardless of your location." [builtin.com](https://builtin.com/company/domino-data-lab)
- **Generous benefits**: Premium medical, dental, and vision insurance (with a free option for family), competitive parental leave, flexible paid time off, annual education reimbursement, and commuter benefits. [domino.ai](https://domino.ai/careers)
- **Culture of ownership**: The company values "low ego and a high degree of ownership," seeking "self-starters" who can "own your outcome." [domino.ai](https://domino.ai/careers)
- **Award-winning workplace**: Domino was named to Inc.’s 2026 Best Workplaces list, signaling strong employee satisfaction and culture. [domino.ai](https://domino.ai/company)
- **Global team with 200+ employees**: A growing, mid-sized company where employees can feel the direct impact of their work. [builtin.com](https://builtin.com/company/domino-data-lab)

## Sources
1. [domino.ai](https://domino.ai/)
2. [domino.ai/company](https://domino.ai/company)
3. [domino.ai/careers](https://domino.ai/careers)
4. [builtin.com](https://builtin.com/company/domino-data-lab)
5. [linkedin.com](https://www.linkedin.com/company/domino-data-lab)

## Other roles at Domino Data Lab

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- [IT Support Engineer](https://feeny.ai/job/it-support-engineer-domino-data-lab-india-eu-south-sq761rmx3bbg) — India EU South, United States
- [Solutions Engineer, Life Sciences](https://feeny.ai/job/solutions-engineer-life-sciences-domino-data-lab-us-east-coast-z9nrq0vj8pyf) — US East Coast
- [Forward Deployed Engineer, Public Sector](https://feeny.ai/job/forward-deployed-engineer-public-sector-domino-data-lab-us-2ag3ghp91nhk) — US, MD
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