Senior Customer Success Manager, Managed Inference

Own strategic relationships with customers running production AI inference workloads and help them achieve performance, reliability, latency, scalability, and cost objectives. Guide model deployment, inference optimization, GPU utilization, autoscaling, observability, and production readiness while monitoring adoption and business outcomes. Coordinate with Product and Engineering, train customers, and advise them during escalations and production events.

Responsibilities

• Develop and maintain strong customer relationships.
• Own strategic relationships with AI-native customers deploying production inference workloads.
• Create case studies highlighting customer successes.
• Act as a liaison between customers and the technical team.
• Provide technical guidance for cloud-based AI and ML solutions, including Kubernetes solutions.
• Partner with customers on model deployment, inference optimization, GPU utilization, autoscaling, throughput management, observability, and production readiness.
• Monitor customer adoption, inference consumption, latency, uptime, capacity utilization, and business outcomes.
• Coordinate customer journeys with Product and Engineering.
• Advocate for customer needs and influence roadmap priorities.
• Maintain awareness of AI technologies and GPU infrastructure trends.
• Deliver customer training sessions and workshops.
• Address and resolve customer concerns.
• Advise customers during escalations, service incidents, and production events.

Requirements

• Bachelor’s degree in Business, Engineering, or a related field.
• Experience in customer success, technical account management, or a similar technology-driven role.
• 3+ years of experience supporting enterprise cloud, AI, machine learning, developer platform, or infrastructure customers.
• Experience managing strategic accounts running production AI workloads.
• Strong foundation in cloud computing, AI, and ML technologies.
• Understanding of inference workloads, model serving architectures, Kubernetes, containers, APIs, GPU infrastructure, and AI application deployment patterns.
• Familiarity with LLMs, RAG architectures, agentic applications, model performance metrics, and inference optimization concepts.
• Excellent interpersonal, communication, and presentation skills.
• Ability to build relationships at all organizational levels.
• Ability to engage executive stakeholders and deeply technical customer teams.
• Ability to work in a fast-paced environment with ambiguous and iterative fact-sets.

Benefits

• Restricted Stock Units
• Paid time off
• Paid holidays
• Leave of absence programs
• Comprehensive health insurance
• Dental insurance
• Vision insurance
• Employer contributions to HSA account
• Paid parental leave
• Paid life insurance
• Short-term disability insurance
• Long-term disability insurance
• Professional development
• Tuition reimbursement
• Mental health and wellness support
• Commuter benefits for parking and transit
• Cell phone stipend
• 401(k) retirement plan with company match up to 4% of salary
• Volunteer time off
• Global travel insurance and emergency assistance
• Daily meals allowance
• Location-specific perks and programs