Customer Success Manager, Managed Inference
Overview
You own customer outcomes for AI inference workloads on Crusoe's cloud platform, guiding enterprise clients from initial deployment to production scale. You bridge technical teams and customer needs, ensuring Kubernetes-based model serving, autoscaling, and observability are optimized for their success. You report to the Customer Experience organization and collaborate with Product and Engineering to shape the managed inference roadmap. This role stands out for its direct impact on cutting-edge AI infrastructure and the opportunity to work with leading AI teams.
What You'll Do6
- 1Build strong customer relationships, acting as a trusted advisor for their technical and business needs during inference deployment.
- 2Guide customers in implementing and tuning Kubernetes, model serving, autoscaling, and observability tools to maximize performance and reliability.
- 3Own quarterly business reviews, tracking adoption, inference consumption, latency, and uptime to flag risks and growth opportunities.
- 4Drive customer advocacy by surfacing platform challenges to Product and Engineering, ensuring your clients' needs shape the roadmap.
- 5Deliver training sessions and workshops to help customers unlock the full value of GPU-based inference and AI services.
- 6Resolve escalations and service incidents with urgency, coordinating with internal teams to restore service and prevent recurrence.
Requirements6
- 12+ years supporting enterprise cloud, AI, ML, or infrastructure customers in customer success or technical account management.
- 2Bachelor's degree in Business, Engineering, or a related field, or equivalent practical experience.
- 3Solid technical foundation in cloud computing platforms, AI, and ML technologies, with ability to explain complex concepts simply.
- 4Working understanding of inference workloads, model serving architectures, Kubernetes, containers, APIs, and GPU infrastructure.
- 5Excellent interpersonal, communication, and presentation skills to engage technical customer teams including AI, ML, and Platform Engineers.
- 6Comfort in fast-paced settings with ambiguous or iterative fact-sets.
Salary Insight
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