Customer Success Engineer
Posted 1 Apr 2026
Advertised as “Senior Customer Success Engineer I ”
BranchFactor Summary
The original posting with the fluff stripped out
- Level
- I
- Expected experience
- 5+ yrs
- Management level
- Individual contributor
- Employment
- Hybrid
No salary listed for this role.
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).