Manager, Customer Success Engineering

DigitalOcean•New York, NY

1d•$125,000 - $153,000•Remote

About The Position

DigitalOcean is seeking a Manager, Customer Success Engineering (AI & Cloud Support) who is passionate about delivering exceptional support experiences and building high-performing teams. In this role, you will operate as a Support Manager leading a team of Customer Success Engineers (CSEs) supporting strategic customers across cloud infrastructure and emerging AI/ML workloads. You will report to the Senior Manager of Customer Success Engineering and own day-to-day support operations, team performance, and customer experience outcomes. This position is focused on driving operational excellence while building strong technical depth within the team across AI, GPUs, Kubernetes, Databases, and core cloud offerings. You will play a key role in ensuring consistent support coverage, developing SMEs, and partnering cross-functionally with Product and Engineering to improve both customer experience and product quality. The ideal candidate will possess a deep understanding of cloud and AI/ML ecosystems, including machine learning operations (MLOps), and enterprise support, combined with a passion for innovation and automation, and a proven ability to lead teams in delivering “white-glove” experiences for strategic customers.

Requirements

5+ years of experience in Technical Support, Customer Success, or Technical Account Management within B2B SaaS, Cloud, or AI/ML environments ideally including experience supporting AI-native, high-growth companies with 24x7 production dependencies on GPU infrastructure.
2+ years of people management experience leading technical, customer-facing teams, preferably in a high-growth, post-acquisition, or rapidly scaling environment.
Solid understanding of AI/ML concepts, including Generative AI, Large Language Models (LLMs), natural language processing (NLP), and MLOps.
Deep familiarity with GPU infrastructure (NVIDIA H100/H200, bare metal GPU provisioning) and AI inference workloads is strongly preferred.
Proficiency in reading and debugging code (Python preferred) and troubleshooting RESTful APIs and cloud architecture.
Excellent verbal and written communication skills, with the ability to translate complex technical or AI concepts for diverse audiences OR to both highly technical engineers and non-technical business executives.
Proven ability to remain calm under pressure and de-escalate high-stakes situations with enterprise clients.

Nice To Haves

Hands-on experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and AI toolchains (e.g., LangChain, Hugging Face).
Experience with major cloud platforms (AWS, Google Cloud, Azure) and their native AI/ML services.
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.
ITIL or equivalent service management certification

Responsibilities

Lead, hire, train, mentor and develop a high-performing team of Customer Success Engineers (CSEs), driving accountability, performance, and career growth
Establish performance metrics (KPIs/SLAs) and conduct regular 1:1s, performance reviews, and career development planning.
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.
Build and strengthen technical expertise within the team across core areas such as Kubernetes (DOKS), Databases, Compute, and AI/ML workloads.
Act as the ultimate point of technical escalation for our largest, most strategic enterprise customers across Cloud and AI/ML workloads, stepping in to manage critical incidents and high-severity (Sev1/Sev2) issues.
Design and implement customized support plans, SLAs, and escalation pathways tailored to the needs of strategic accounts.
Partner closely with Technical Account Managers (TAMs), Growth Account Managers (GAM) to conduct Executive Business Reviews (EBRs) and ensure customers are maximizing the value of our Cloud and AI/ML products.
Proactively identify risks and opportunities within strategic accounts to improve customer experience, adoption, and retention.
Serve as the Voice of the Customer (VoC) to Product and Engineering teams, synthesizing support data to advocate for bug fixes, feature requests, and UX improvements.
Own and continuously improve escalation protocols between AI/ML Support and CloudOps, Infrastructure Engineering, and Product — including Jira escalation routing, Sev1 bridge management, and post-incident documentation.
Own the development and maintenance of SOPs, escalation runbooks, HVC support playbooks, and knowledge base content — treating documentation infrastructure 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 to improve efficiency, scalability, and customer experience.
Foster a culture of continuous learning, ensuring the team stays ahead of evolving cloud technologies, AI/ML frameworks, and industry trends.