DigitalOcean
Overview
Join to apply for the
Senior Customer Success Engineer
role at
DigitalOcean Dive in and do the best work of your career at DigitalOcean. We value growth mindset, bold thinking, and a fast-paced, industry-disruptive environment. We aim to support builders and dreamers who want to simplify cloud and scale AI/ML workloads. 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 that values ownership, bold thinking, and a strong focus on customer success. We prioritize career development. Access to conferences, training, education reimbursements, and LinkedIn Learning for ongoing growth. We care about well-being. Competitive benefits, remote-friendly policies, and flexibility where available. We reward our employees. Competitive salary, potential bonuses, and equity compensation. We value diversity and inclusion. We are an equal-opportunity employer and strive for an inclusive environment.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Information Technology, Customer Service, and Engineering
Industries
Internet Publishing
#J-18808-Ljbffr
Join to apply for the
Senior Customer Success Engineer
role at
DigitalOcean Dive in and do the best work of your career at DigitalOcean. We value growth mindset, bold thinking, and a fast-paced, industry-disruptive environment. We aim to support builders and dreamers who want to simplify cloud and scale AI/ML workloads. 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 that values ownership, bold thinking, and a strong focus on customer success. We prioritize career development. Access to conferences, training, education reimbursements, and LinkedIn Learning for ongoing growth. We care about well-being. Competitive benefits, remote-friendly policies, and flexibility where available. We reward our employees. Competitive salary, potential bonuses, and equity compensation. We value diversity and inclusion. We are an equal-opportunity employer and strive for an inclusive environment.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Information Technology, Customer Service, and Engineering
Industries
Internet Publishing
#J-18808-Ljbffr