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DigitalOcean

Senior Customer Success Engineer

Reposted 5 Days Ago
Be an Early Applicant
In-Office
Seattle, WA
87K-131K Annually
Senior level
In-Office
Seattle, WA
87K-131K Annually
Senior level
As a Senior Customer Success Engineer, you will provide advanced support for Kubernetes and AI/ML workloads, troubleshooting and guiding customers to optimize their experiences with DigitalOcean's cloud platform.
The summary above was generated by AI

Dive in and do the best work of your career at DigitalOcean. Journey alongside a strong community of top talent who are relentless in their drive to build the simplest scalable cloud. If you have a growth mindset, naturally like to think big and bold, and are energized by the fast-paced environment of a true industry disruptor, you’ll find your place here.  We value winning together—while learning, having fun, and making a profound difference for the dreamers and builders in the world. 

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.
Compensation Range: 
  • $93,000 - $117,000

*This is a remote role

#LI-Remote

Why You’ll Like Working for DigitalOcean
  • We innovate with purpose. You’ll be a 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. As a member of the team, you will be a Shark who thinks big, bold, and scrappy, like an owner with a bias for action and a powerful sense of responsibility for customers, products, employees, and decisions.
  • We prioritize career development. At DO, you’ll do the best work of your career. You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that will always challenge you to think big. Our organizational development team will provide you with resources to ensure you keep growing. We provide employees with reimbursement for relevant conferences, training, and education. All employees have access to LinkedIn Learning's 10,000+ courses to support their continued growth and development.
  • We care about your well-being. Regardless of your location, we will provide you with a competitive array of benefits to support you from our Employee Assistance Program to Local Employee Meetups to flexible time off policy, to name a few. While the philosophy around our benefits is the same worldwide, specific benefits may vary based on local regulations and preferences.
  • We reward our employees. The salary range for this position is based on market data, relevant years of experience, and skills. You may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program.
  • DigitalOcean is an equal-opportunity employer. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Top Skills

Ai/Ml Workloads
Docker
Gpu Infrastructure
Grafana
Kubernetes
Linux
Opentelemetry
Prometheus
PyTorch
TensorFlow

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