Senior Customer Success Manager

Responsibilities

• Develop and maintain strong, long-lasting customer relationships, understanding business needs and technical requirements
• Own strategic relationships with AI-native customers deploying production inference workloads
• Act as a technical liaison between clients and internal technical teams
• Provide technical guidance on cloud-based AI/ML solutions, including Kubernetes, model deployment, and GPU utilization
• Monitor customer adoption, inference consumption, latency metrics, and capacity utilization
• Partner with Product and Engineering teams to advocate for customer needs and influence roadmap priorities
• Deliver training sessions and workshops to customers
• Act as a trusted advisor during customer escalations and critical production events

Requirements

• Bachelor’s degree in Business, Engineering, or a related field
• 3+ years of experience supporting enterprise cloud, AI, machine learning, developer platform, or infrastructure customers
• Strong technical foundation in cloud computing, AI, and ML technologies
• Understanding of inference workloads, model serving architectures, Kubernetes, containers, APIs, and GPU infrastructure
• Excellent interpersonal, communication, and presentation skills
• Ability to engage with both executive stakeholders and technical teams like AI/ML Engineers

Preferred Qualifications

• Advanced degree
• Experience managing strategic accounts running production AI workloads
• Familiarity with LLMs, RAG architectures, agentic applications, and inference optimization

Benefits

• Competitive compensation and equity packages (RSUs)
• Comprehensive health, dental, and vision insurance
• 401(k) Retirement plan with company match up to 4%
• Paid parental leave and volunteer time off
• Professional development and tuition reimbursement
• Daily meals allowance and cell phone stipend

About the Company

Crusoe is a vertically integrated AI infrastructure company that owns and operates each layer of the stack to power the world's most ambitious AI workloads using an energy-first approach.