Senior Customer Success Manager, Managed Inference
$190,000–$215,000 year
On-siteSan Francisco, California, United States
Job Summary
Own strategic relationships with AI-native customers deploying production inference workloads, guiding them through technical complexities to achieve performance, reliability, latency, and cost optimization objectives. Provide technical guidance on model deployment, Kubernetes solutions, GPU utilization, and observability while monitoring adoption trends and business outcomes. Act as a trusted advisor during escalations and critical production events, delivering training sessions to empower clients. Coordinate with Product and Engineering teams to define customer journeys and influence roadmap priorities for inference platforms. Maintain deep industry awareness of LLMs, agentic workflows, and model serving architectures to provide strategic advice.
Required Qualifications
- Bachelor's degree in Business, Engineering, or a related field
- Advanced degree
- Proven experience in customer success, technical account management, or a similar role in a technology-driven environment
- 3+ years of experience supporting enterprise cloud, AI, machine learning, developer platform, or infrastructure customers
- Strong technical foundation in cloud computing platforms, AI, and ML technologies
- Strong understanding of inference workloads, model serving architectures, Kubernetes, containers, APIs, GPU infrastructure, and AI application deployment patterns
Desired Qualifications
- Experience supporting Managed Inference, model serving platforms, LLM deployments, AI agents, or GPU-based inference environments
- Experience managing strategic accounts running production AI workloads
- Familiarity with LLMs, RAG architectures, agentic applications, model performance metrics, and inference optimization concepts
- Excellent interpersonal, communication, and presentation skills
- Demonstrated ability to build relationships at all levels within an organization
- Ability to engage effectively with both executive stakeholders and deeply technical customer teams, including AI Engineers, ML Engineers, Platform Engineers, and Infrastructure leaders
- Comfortable working in a fast-paced environment with ambiguous and/or iterative fact-sets
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