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Job description
Our mission at Tensorwave Cloud is to build seamless, secure, reliable, and resilient AI infrastructure at scale, eliminating barriers and challenging the status quo to empower builders and support AI innovation.
About The Role
We’re seeking a Head of Customer Experience to build and lead TensorWave’s customer organization as we scale our AMD-powered AI infrastructure platform.
You will own customer satisfaction, retention, and expansion across AI startups, ML teams, and Fortune 500 customers.
This is a senior leadership role responsible for building high-performing customer teams, establishing scalable customer success processes, and serving as an executive sponsor for strategic accounts running large-scale training and inference workloads.
You will partner closely with company leadership, develop strong C-suite relationships, and ensure customer success becomes a durable, measurable function as TensorWave grows.
Responsibilities
Define and execute TensorWave's hypergrowth customer operations strategy
Build, mentor, and scale a high-performing organization of technical customer success managers and operations professionals
Design and optimize the customer journey from POC/evaluation through production deployment, scaling, renewal, and expansion.
Lead quarterly business reviews and strategic planning sessions with customer Engineering stakeholders
Act as voice of the customer within TensorWave, advocating for needs related to AMD GPU performance, ROCm software stack, platform features, and infrastructure scaling
Proactively identify at-risk enterprise accounts based on utilization patterns, support tickets, or competitive pressures and orchestrate recovery strategies
Develop and lead customer advisory boards, executive forums, and industry working groups to strengthen TensorWave's position in the AI infrastructure ecosystem
Recruit, develop, and retain top-tier customer success talent with strong technical backgrounds in AI/ML infrastructure, GPU computing, and cloud platforms
Design scalable processes, runbooks, and best practices for managing enterprise customers with diverse workloads (LLM training, inference, fine-tuning, HPC)
Implement robust performance management frameworks with clear metrics around customer health, GPU utilization, expansion pipeline, and NRR
Deploy and optimize customer success platforms integrated with usage analytics, GPU telemetry, and business intelligence systems
Partner with Sales on seamless handoffs, technical account planning, competitive displacement strategies (NVIDIA to AMD), and enterprise sales cycles
Collaborate with Product and Engineering to translate customer feedback on AMD GPU performance, ROCm compatibility, platform features, and infrastructure needs into roadmap priorities
Build strong partnerships with Sales, Product, Marketing, Engineering, Operations, and within the broader AMD ecosystem.
Contribute to board and executive level reporting on customer metrics.
Required Experience
Bachelor of Science in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience
7+ years of experience in customer success, enterprise account management, or solutions engineering roles in cloud infrastructure, GPU computing, or AI/ML platforms
5+ years of people management experience, including managing managers and building high-performing teams from scratch
Proven track record leading customer success at scale in high-growth infrastructure or platform companies
Strong technical fluency with cloud computing, GPU architecture, and AI/ML workload
Ability to engage credibly with customer ML engineers and infrastructure teams
Exceptional executive presence with ability to engage and influence C-level and VP-level engineering/technical stakeholders
Strategic thinker with strong business acumen, analytical capabilities, and data-driven decision-making approach
Outstanding communication and presentation skills with ability to inspire teams, influence cross-functionally, and represent TensorWave at industry events
Experience building scalable CS operations, implementing health scoring systems, and establishing data-driven customer engagement models
Track record of recruiting, developing, and retaining high-performing teams in competitive talent markets
Preferred Experience
MBA or advanced technical degree (MS in CS, ML, or related field)
Hands-on experience with GPU computing (AMD Instinct, NVIDIA A100/H100) and understanding of AI/ML training and inference workloads
Familiarity with AMD ROCm ecosystem, PyTorch, TensorFlow, HuggingFace, and LLM training/fine-tuning workflows
Experience in neocloud, alternative cloud providers, or companies disrupting incumbent markets
Background in technical pre-sales, solutions architecture, or DevOps/ML engineering
Experience managing customer relationships during platform migrations or competitive displacement scenarios (especially NVIDIA to AMD transitions)
Strong network in AI/ML, cloud infrastructure, or HPC communities
Prior experience at high-growth startups that scaled from Series A to IPO or acquisition
What We Bring
Mission driven company
Competitive Salary
Stock Options
100% paid Medical, Dental, and Vision insurance
Flexible PTO
Paid Holidays
401(k)
Parental Leave
Flexible Spending Account
Short Term Disability Insurance
Life and Voluntary Supplemental Insurance
Mental Health Benefits through Spring Health
We’re looking for resilient, adaptable people to join our team, people who believe in the mission and think at massive scale. The solutions that worked on a handful of devices will not work at Exascale. Be prepared to be pushed daily, to learn a lot, and literally build the future.
Tensorwave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, national origin, or veteran status.
About the company
TensorWave
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Worksite address
las vegas, NV, 89105, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.