Senior Customer Success Engineer I

DigitalOcean
Hyderabad, India
On-site

Who this role is best for

A natural match if you have deep Kubernetes and AI/ML infrastructure expertise.

Best fit for

  • Candidates with 5+ years in technical support and production Kubernetes experience
    — “5+ years in technical support, DevOps, solutions engineering, or SRE roles.”
  • Individuals with proven ability to troubleshoot complex AI/ML and GPU environments
    — “Experience supporting AI/ML workflows using GPUs (e.g., NVIDIA A100, L4, CUDA, TensorFlow, PyTorch).”

Things to consider

  • Application limit of 3 roles within 180 days may affect submission frequency
    — “You may apply to a maximum of 3 positions within any 180-day period.”
  • Role requires independent work in a remote setup, with potential for high responsibility
    — “Comfortable working independently and collaboratively in a remote environment.”

How to stand out

  • Highlight white-glove support experience with high-value customers
    — “Engage directly with our strategic and high-value customers via tickets, Slack, email, and live sessions.”
  • Demonstrate your ability to shape internal documentation and processes
    — “Help shape internal runbooks, SOPs, and documentation to scale AI/ML and GPU-related support.”
  • Showcase your influence on product and engineering teams through feedback
    — “Partner with Engineering and Product teams to provide feedback on platform usability, bugs, and customer needs.”
  • Emphasize your hands-on experience with AI/ML tools like Kubeflow or Ray
    — “Hands-on experience with Paperspace, JupyterHub, Kubeflow, or Ray.”
  • Demonstrate your ability to communicate technical complexity to non-technical stakeholders
    — “Ability to communicate complex technical topics clearly to customers and cross-functional stakeholders.”
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • troubleshoot and resolve advanced support cases
  • provide feedback on platform usability
  • shape internal runbooks and SOPs
  • participate in incident management
  • educate and mentor internal team members
Typical background
5+ years in technical support, DevOps, solutions engineering, or SRE roles

Skills & requirements

Required

KubernetesAi/ml WorkloadsGPU InfrastructureTechnical SupportPlatform Usability FeedbackIncident ManagementArchitecture And OptimizationEducation And Mentorship

Preferred

Cloud-native Observability StacksPaperspaceJupyterhubKubeflowRayNetworking Topics

Stack & domain

KubernetesAi/ml WorkloadsGPU InfrastructureTechnical SupportDevOpsSolutions EngineeringSREContainer Lifecycle ManagementGPU SchedulingScaling AI JobsLinux Systems AdministrationShell ScriptingPerformance TuningBare MetalVirtualized EnvironmentsCloud-native Observability StacksPaperspaceJupyterhubKubeflowRayNetworking TopicsCNI PluginsOverlay NetworksIngress ControllersCustomer-facing RolesIaas/paas ProvidersML Ops PlatformsCommunicationProblem-solvingAttention To DetailCka-certifiedCloud ComputingAIGPUAi/mlGpu-backed InfrastructureLinuxContainerOrchestrationNetworkingStorageRemote Environment

About the role

Original posting from DigitalOcean

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 Senior Customer Success Engineer SME with a minimum 5 years of experience and 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 Senior Customer Success 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.

JR: [2026-7644]

#LI-Hybrid

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.

Application Limit: You may apply to a maximum of 3 positions within any 180-day period. This policy promotes better role-candidate matching and encourages thoughtful applications where your qualifications align most strongly.

Source: DigitalOcean careers

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