Technical Account Manager - AI Infrastructure

Responsibilities

• Own a portfolio of enterprise customers end-to-end — adoption, retention, expansion, and overall health
• Build deep relationships with technical and executive stakeholders at each customer, from ML engineers to engineering leadership
• Drive customer outcomes: faster time-to-value on first workloads, smooth scaling as their usage grows, and meaningful expansion as their AI ambitions expand
• Understand each customer's training and inference workloads at a real technical level — what models they're training, what infrastructure they need, what their performance bottlenecks are
• Partner with customers' engineering teams on cluster performance, capacity planning, workload optimization, and migration
• Translate customer needs into clear, prioritized feedback for our Engineering and Product teams
• Identify expansion opportunities ahead of the customer — anticipate scaling needs, surface new use cases, drive adoption of new products (Lab, Inference, additional compute capacity)
• Partner with Sales on renewal conversations and growth motions
• Maintain visibility into the economics of each customer relationship, in partnership with Finance and Compute
• Serve as the first line for customer-facing operational issues — usage questions, capacity changes, SLA tracking, incident communications
• Build the cross-functional connective tissue between Sales, Engineering, Finance, and customers

Qualifications

• 3–6 years in Customer Success, Technical Account Management, Solutions Engineering, or adjacent roles at infrastructure, cloud, or AI/ML companies
• Strong technical fluency — comfortable reading dashboards, discussing infrastructure architecture, and engaging with customer engineering teams without a translator
• Strong commercial instincts — you understand that Customer Success is a revenue function, not a support function, and you can drive real expansion alongside technical outcomes
• Deep customer empathy combined with high judgment — you advocate for customers internally while making the calls that are right for the business
• Excellent verbal and written communication, especially when explaining complex technical issues to non-technical stakeholders and vice versa
• High ownership — you see gaps and build the fix before anyone asks
• Comfortable in ambiguity and speed; this market doesn't slow down
• AI-native in how you work: you use LLMs, automation, and programmatic tools to move faster