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DigitalOcean

Runs cloud infrastructure for apps and AI

Senior Customer Success Engineer

Solution EngineeringConfirmed live in the last 24 hours
Full-timeHyderabad, Telangana, IndiaIn-person

About the Job

Requirements

  • A minimum of 5 years in technical support, DevOps, solutions engineering, or Site Reliability Engineering roles.
  • Deep experience with Kubernetes, preferably with CKA certification, in production environments.
  • Experience supporting artificial intelligence and machine-learning workflows using GPUs such as NVIDIA A100, L4, CUDA, TensorFlow, or PyTorch.
  • Familiarity with container lifecycle management, GPU scheduling, and scaling artificial intelligence jobs in Kubernetes.
  • Advanced knowledge of Linux systems administration with Ubuntu or 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, including containers, orchestration, networking, and storage.
  • Ability to work independently and collaboratively in a remote environment.

Responsibilities

  • Act as a technical subject matter expert for Kubernetes, artificial intelligence and machine-learning 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 strategic and high-value customers through 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, standard operating procedures, and documentation to scale artificial intelligence, machine-learning, 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.

Desired Qualifications

  • Familiarity with cloud-native observability stacks such as Prometheus, Grafana, and OpenTelemetry.
  • Hands-on experience with Paperspace, JupyterHub, Kubeflow, or Ray.
  • Exposure to networking topics such as Container Network Interface plugins, overlay networks, and ingress controllers.
  • Prior experience in customer-facing roles at Infrastructure-as-a-Service or Platform-as-a-Service providers or machine-learning operations platforms.

About the Company

DigitalOcean

Runs cloud infrastructure for apps and AI

DigitalOcean provides cloud infrastructure for developers and businesses to build, host and scale applications and AI services. Teams rent virtual machines called Droplets, store data and run managed databases or Kubernetes clusters through a web console and APIs. Its AI services supply GPU computing, model inference and managed environments where software agents use tools and retain information between sessions. Customers pay for the resources they use, with subscriptions and managed services helping teams run applications without maintaining all the underlying infrastructure themselves. DigitalOcean was founded in 2012 and is headquartered in Broomfield, Colorado.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Broomfield, CO
Founded
2012

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