Senior Technical Support Engineer
Provides hands-on technical support for enterprise customers using Kubernetes, cloud infrastructure, and ML platforms. The role requires strong Linux and troubleshooting skills, customer-facing communication, and 3–5 years of relevant experience.
About the job
Responsibilities
- Own enterprise customer support cases across all severity levels, from initial triage through resolution, with clear communication and accurate expectations.
- Diagnose and resolve Kubernetes and cloud infrastructure issues, including pod failures, resource limits, persistent volumes, RBAC, ingress, and cluster-level diagnostics.
- Troubleshoot ML platform issues such as workspace and job failures, environment build errors, model deployment problems, and data connector failures.
- File detailed bug reports and enhancement requests in Jira, advocating for customers with Product and Engineering.
- Write and review knowledge base articles, how-to guides, and troubleshooting documentation.
- Hand off cases across AMER, EMEA, and APAC in a follow-the-sun model.
- Run live customer troubleshooting sessions and participate in the EMEA weekend on-call rotation.
Requirements
- 3–5 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 troubleshooting. - Strong Linux and command-line proficiency, including log analysis, process management, filesystem 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 strong written communication skills.
- Ability to manage multiple time-sensitive cases and collaborate asynchronously across time zones.
- Bachelor's degree in computer science, engineering, or a related technical field, or equivalent experience.
Compensation & Benefits
- Remote-first, globally distributed team.
- EMEA weekend on-call rotation per team schedule.
Skills
Kubernetes, Kubectl, RBAC, Persistent Volumes, Linux, Shell Scripting, Python, Jupyter, Machine Learning, AWS, GCP, Azure, Jira, Docker
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