Manager, Customer Success Engineering

DigitalOcean is looking for a Manager, Customer Success Engineering (AI & Cloud Support) who is passionate about delivering exceptional support experiences and building high-performing teams. You will operate as a Support Manager leading a team of Customer Success Engineers supporting strategic customers across cloud infrastructure and emerging AI/ML workloads, owning day-to-day support operations, team performance, and customer experience outcomes. The role centers on operational excellence while building technical depth across AI, GPUs, Kubernetes, Databases, and core cloud offerings, with a strong pull toward automation-first support.

Key Responsibilities:

• Lead, hire, train, mentor, and develop a high-performing team of Customer Success Engineers, driving accountability, performance, and career growth.
• Own end-to-end support operations, including queue management, escalations, and shift planning to ensure consistent 24x7 coverage.
• Drive improvements in key support metrics such as CSAT, response times, resolution times, and overall support quality.
• Act as the ultimate point of technical escalation for the largest, most strategic enterprise customers, stepping in to manage critical incidents and high-severity issues.
• Design and implement customized support plans, SLAs, and escalation pathways tailored to strategic accounts.
• Serve as the Voice of the Customer to Product and Engineering, synthesizing support data to advocate for bug fixes, feature requests, and UX improvements.
• Own the development of SOPs, escalation runbooks, and knowledge base content, treating documentation as a core operational lever for team scalability.
• Contribute to the vision for AI and automation within support, building intelligent tooling and driving the team toward an automation-first model.

Qualifications:

• 5+ years in Technical Support, Customer Success, or Technical Account Management within B2B SaaS, Cloud, or AI/ML environments.
• 2+ years of people management experience leading technical, customer-facing teams.
• Solid understanding of AI/ML concepts, including Generative AI, LLMs, NLP, and MLOps; deep familiarity with GPU infrastructure (NVIDIA H100/H200, bare metal provisioning) and AI inference workloads is strongly preferred.
• Proficiency in reading and debugging code (Python preferred) and troubleshooting RESTful APIs and cloud architecture.
• Proven ability to remain calm under pressure and de-escalate high-stakes situations with enterprise clients.
• Preferred: hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn), AI toolchains (LangChain, Hugging Face), and major cloud platforms.