DigitalOcean
Senior Customer Success Engineer
DigitalOcean, San Francisco, California, United States, 94199
Overview
Join to apply for the
Senior Customer Success Engineer
role at
DigitalOcean . We are looking for a Cloud Support Engineer SME with deep expertise in Kubernetes, AI/ML workloads, and GPU infrastructure who is passionate about helping our customers scale and innovate with cutting-edge technologies. As a
Cloud Support Engineer
at DigitalOcean, you will join a dynamic team dedicated to revolutionizing cloud computing and AI. You will be a key member of our advanced support team, helping DigitalOcean's strategic customers succeed by providing white-glove support and guidance across complex technical domains. Reporting to the Manager of Customer Success Engineering, you’ll act as both a trusted advisor and a technical troubleshooter, empowering our customers to build and scale confidently on our platform. What You’ll Do
Act as a technical subject matter expert (SME) for Kubernetes, AI/ML workloads, and GPU-backed infrastructure. Troubleshoot and resolve advanced support cases related to orchestration, performance tuning, container networking, and GPU-based compute. Engage directly with our strategic and high-value customers via tickets, Slack, email, and live sessions. Partner with Engineering and Product teams to provide feedback on platform usability, bugs, and customer needs. Help shape internal runbooks, SOPs, and documentation to scale AI/ML and GPU-related support. Participate in incident management, root cause analysis, and retrospective reviews. Contribute to the architecture and optimization of customer workloads for high availability and cost efficiency. Educate and mentor internal team members on Kubernetes and GPU-based architectures. Influence roadmap priorities by surfacing recurring pain points and opportunities. What You’ll Add To DigitalOcean
5+ years in technical support, DevOps, solutions engineering, or SRE roles. Deep experience with Kubernetes (preferably CKA-certified) in production environments. Experience supporting AI/ML workflows using GPUs (e.g., NVIDIA A100, L4, CUDA, TensorFlow, PyTorch). Familiarity with container lifecycle management, GPU scheduling, and scaling AI jobs in Kubernetes. Advanced knowledge of Linux systems administration (Ubuntu/Debian), shell scripting, and performance tuning. Deep knowledge of Bare Metal and Virtualized environments. Ability to communicate complex technical topics clearly to customers and cross-functional stakeholders. Experience troubleshooting full-stack deployments—containers, orchestration, networking, and storage. Comfortable working independently and collaboratively in a remote environment. Bonus Points For
Familiarity with cloud-native observability stacks (Prometheus, Grafana, OpenTelemetry). Hands-on experience with Paperspace, JupyterHub, Kubeflow, or Ray. Exposure to networking topics like CNI plugins, overlay networks, and ingress controllers. Prior experience in customer-facing roles at IaaS/PaaS providers or ML Ops platforms. Why You’ll Like Working for DigitalOcean
We innovate with purpose. You’ll be part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. We prioritize career development. You’ll do the best work of your career. We support growth with conferences, training, and LinkedIn Learning access. We care about your well-being. We offer a competitive benefits package and flexible time off policy; benefits may vary by location. We reward our employees. Salary range is $87,200 - $109,000 with potential bonuses and equity opportunities; eligibility for Employee Stock Purchase Program. We value diversity and inclusion. We are an equal-opportunity employer and do not discriminate on various protected characteristics. This is a remote role. Seniority level
Mid-Senior level Employment type
Full-time Job function
Information Technology, Customer Service, and Engineering Industries: Internet Publishing This description reflects the responsibilities and qualifications for the Senior Customer Success Engineer role at DigitalOcean. It omits extraneous recruiter chatter and unrelated postings.
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Join to apply for the
Senior Customer Success Engineer
role at
DigitalOcean . We are looking for a Cloud Support Engineer SME with deep expertise in Kubernetes, AI/ML workloads, and GPU infrastructure who is passionate about helping our customers scale and innovate with cutting-edge technologies. As a
Cloud Support Engineer
at DigitalOcean, you will join a dynamic team dedicated to revolutionizing cloud computing and AI. You will be a key member of our advanced support team, helping DigitalOcean's strategic customers succeed by providing white-glove support and guidance across complex technical domains. Reporting to the Manager of Customer Success Engineering, you’ll act as both a trusted advisor and a technical troubleshooter, empowering our customers to build and scale confidently on our platform. What You’ll Do
Act as a technical subject matter expert (SME) for Kubernetes, AI/ML workloads, and GPU-backed infrastructure. Troubleshoot and resolve advanced support cases related to orchestration, performance tuning, container networking, and GPU-based compute. Engage directly with our strategic and high-value customers via tickets, Slack, email, and live sessions. Partner with Engineering and Product teams to provide feedback on platform usability, bugs, and customer needs. Help shape internal runbooks, SOPs, and documentation to scale AI/ML and GPU-related support. Participate in incident management, root cause analysis, and retrospective reviews. Contribute to the architecture and optimization of customer workloads for high availability and cost efficiency. Educate and mentor internal team members on Kubernetes and GPU-based architectures. Influence roadmap priorities by surfacing recurring pain points and opportunities. What You’ll Add To DigitalOcean
5+ years in technical support, DevOps, solutions engineering, or SRE roles. Deep experience with Kubernetes (preferably CKA-certified) in production environments. Experience supporting AI/ML workflows using GPUs (e.g., NVIDIA A100, L4, CUDA, TensorFlow, PyTorch). Familiarity with container lifecycle management, GPU scheduling, and scaling AI jobs in Kubernetes. Advanced knowledge of Linux systems administration (Ubuntu/Debian), shell scripting, and performance tuning. Deep knowledge of Bare Metal and Virtualized environments. Ability to communicate complex technical topics clearly to customers and cross-functional stakeholders. Experience troubleshooting full-stack deployments—containers, orchestration, networking, and storage. Comfortable working independently and collaboratively in a remote environment. Bonus Points For
Familiarity with cloud-native observability stacks (Prometheus, Grafana, OpenTelemetry). Hands-on experience with Paperspace, JupyterHub, Kubeflow, or Ray. Exposure to networking topics like CNI plugins, overlay networks, and ingress controllers. Prior experience in customer-facing roles at IaaS/PaaS providers or ML Ops platforms. Why You’ll Like Working for DigitalOcean
We innovate with purpose. You’ll be part of a cutting-edge technology company with an upward trajectory, who are proud to simplify cloud and AI so builders can spend more time creating software that changes the world. We prioritize career development. You’ll do the best work of your career. We support growth with conferences, training, and LinkedIn Learning access. We care about your well-being. We offer a competitive benefits package and flexible time off policy; benefits may vary by location. We reward our employees. Salary range is $87,200 - $109,000 with potential bonuses and equity opportunities; eligibility for Employee Stock Purchase Program. We value diversity and inclusion. We are an equal-opportunity employer and do not discriminate on various protected characteristics. This is a remote role. Seniority level
Mid-Senior level Employment type
Full-time Job function
Information Technology, Customer Service, and Engineering Industries: Internet Publishing This description reflects the responsibilities and qualifications for the Senior Customer Success Engineer role at DigitalOcean. It omits extraneous recruiter chatter and unrelated postings.
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