Senior Technical Account Manager

GMI Cloud; Mountain View (CA); On-site; USD 140,000 - 180,000; Full time

Job summary

GMI Cloud is seeking a Senior Technical Account Manager to own the technical relationship with enterprise customers, guiding deployment, operation, and scaling of cloud workloads. You will coordinate cross‑functional teams to resolve issues, drive success plans, and ensure long-term value from our GPU/cloud platform.

The role requires deep Kubernetes expertise, strong customer-management skills, and the ability to translate complex technical concepts for diverse stakeholders while accelerating

Qualifications

• 5+ years in Technical Account Management or similar customer-facing technical role.
• Demonstrated enterprise customer relationship ownership.
• Strong hands-on Kubernetes knowledge and cloud-native tech.

Responsibilities

• Serve as primary technical contact for assigned customers throughout their lifecycle.
• Lead technical reviews, check-ins, and success planning sessions.
• Advocate for customers and translate feedback into product/engineering actions.
• Coordinate cross-functional responses to incidents and optimize cloud workloads.

Skills

Kubernetes

Cloud infrastructure

Technical account management

Customer success

Stakeholder management

Education

Bachelor's degree in CS/Engineering

Tools

Ceph storage

NVMe

NFS

InfiniBand

Job description

GMI Cloud is a fast-growing AI infrastructure company backed by Headline VC and one of only six cloud providers worldwide to earn NVIDIA’s prestigious Reference Platform Cloud Partner designation. We operate eight GPU clusters across the U.S. and Asia, delivering a full spectrum of services—from GPU compute to AI model inference APIs.

Our infrastructure meets rigorous standards for performance, security, and scalability in AI deployments. We empower AI startups and enterprises to “build AI without limits,” providing the infrastructure and services they need to prototype, train, and deploy AI models quickly and reliably.

About the Role

We are seeking a Senior Technical Account Manager (TAM) with a strong background in technical account management or customer success and deep hands‑on knowledge of Kubernetes.

In this role, you will serve as a trusted technical advisor to our customers, helping them successfully deploy, operate, and scale cloud‑based workloads. You will own the technical customer relationship, proactively identify risks, coordinate issue resolution, and ensure customers receive long‑term value from GMI Cloud’s platform.

The ideal candidate combines strong customer management skills with practical cloud‑native infrastructure expertise. Prior experience with GPU cloud, AI infrastructure, or large‑scale AI/ML workloads is highly valued but not required.

Key Responsibilities

Customer Success and Relationship Management

• Serve as the primary technical point of contact for assigned customers throughout their lifecycle.
• Build trusted relationships with technical stakeholders, engineering teams, and business leaders.
• Develop a deep understanding of each customer’s technical environment, business objectives, and success criteria.
• Lead regular customer check‑ins, technical reviews, and success planning sessions.
• Advocate for customers internally and translate customer feedback into actionable recommendations for Product, Engineering, and Operations teams.
• Identify adoption risks, expansion opportunities, and areas where customers may need additional technical guidance.

Technical Guidance and Issue Resolution

• Advise customers on deploying, operating, and scaling Kubernetes‑based workloads.
• Help customers troubleshoot Kubernetes issues involving deployment, scheduling, networking, storage, observability, and resource management.
• Coordinate cross‑functional responses to technical incidents and ensure issues are communicated, escalated, and resolved effectively.
• Conduct root‑cause follow‑ups and help customers implement preventative measures.
• Deliver technical workshops, enablement sessions, and tailored consultations based on customer needs.

Cloud Optimization and Operational Excellence

• Conduct operational and architecture reviews to identify opportunities for improved reliability, scalability, performance, and cost efficiency.
• Help customers strengthen monitoring, business continuity, disaster recovery, and capacity‑planning practices.
• Support cloud onboarding and migration initiatives, including workload readiness and deployment planning.
• Guide customers toward cloud‑native operational best practices and greater self‑sufficiency.
• Partner with internal teams to continuously improve customer experience, support processes, and platform capabilities.

Required Qualifications

• 5+ years of experience in Technical Account Management, Technical Customer Success, Customer Engineering, Solutions Architecture, or a similar customer‑facing technical role.
• Demonstrated experience owning relationships with enterprise or technically sophisticated customers.
• Strong hands‑on knowledge of Kubernetes, including container orchestration, workload scheduling, networking, storage, troubleshooting, and cluster operations.
• Solid understanding of cloud infrastructure and cloud‑native technologies.
• Experience managing technical escalations and coordinating across Engineering, Product, Support, and Operations teams.
• Ability to translate complex technical concepts into clear recommendations for both technical and non‑technical stakeholders.
• Strong customer‑first mindset with excellent communication, stakeholder management, and problem‑solving skills.
• Ability to operate effectively in a fast‑paced and rapidly evolving environment.

Preferred Qualifications

• Experience supporting customers at an AI cloud, GPU cloud, cloud infrastructure, or developer platform company.
• Familiarity with GPU infrastructure, including GPU servers, storage technologies such as Ceph, NVMe, and NFS, or high‑speed networking such as InfiniBand and RoCE.
• Understanding of AI/ML or large language model training and inference workflows.
• Familiarity with tools such as vLLM, SGLang, Slurm, Ray, or similar distributed computing technologies.
• Experience supporting HPC, MLOps, distributed computing, or large‑scale AI infrastructure environments.
• Experience conducting technical workshops, operational reviews, or customer enablement programs.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.