Head of Customer Experience

About TensorWave

Our mission is simple: deliver seamless, secure, reliable, and resilient AI compute at scale. We've built a versatile cloud platform that eliminates infrastructure barriers, empowering builders to focus on innovation instead of fighting their stack. Because breakthrough AI should move at the speed of ideas, not infrastructure.

About the Role

We’re looking for a Head of Customer Experience to join our team during an exciting phase of growth. In this role, you’ll be responsible for owning customer satisfaction, retention, and expansion, working closely with cross-functional partners to support business objectives while upholding our standards for excellence, collaboration, and impact.

What You’ll Do

• 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

Who You Are

Required Qualifications

• 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 Qualifications

• 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