Customer Success Manager (San Francisco Bay Area)

Our client is a fast-growing AI infrastructure company that provides a real-time web search platform for enterprise businesses and AI systems. We are looking for a Strategic Customer Success Manager to manage and grow enterprise customer relationships in the United States.

This is a strategic, customer-facing post-sales role focused on adoption, retention, renewals and revenue expansion. You will act as a trusted advisor to enterprise customers, ensure they achieve measurable business value, and identify opportunities to expand accounts. You will manage a portfolio of about 30 enterprise customers (roughly $3M to $4M combined) and work closely with Product, Support and Engineering.

Set-up: On-site, 5 days a week, in the San Francisco Bay Area.
Compensation: $180,000 to $230,000 OTE (approximately 70% base, 30% variable, with some flexibility on a higher base), depending on experience and qualifications.

Key Responsibilities

• Manage and grow a portfolio of about 30 enterprise customers (about $3M to $4M combined)
• Own customer relationships across the post-sales lifecycle: adoption, retention, renewals and expansion
• Act as a trusted advisor to enterprise customers and deliver measurable business value
• Troubleshoot technical issues hands-on using APIs, logs, integrations and workflows
• Manage relationships with technical and business stakeholders, including Engineering, Data, AI, Product and BI teams, and senior or C-level executives
• Run Quarterly Business Reviews (QBRs) and Executive Business Reviews (EBRs) covering business impact, ROI, adoption metrics and strategic recommendations
• Monitor customer health, identify risks and prevent churn
• Drive account expansion, upsell and cross-sell, and own retention and growth targets
• Build business cases and demonstrate measurable ROI
• Develop long-term account strategies
• Work with Product, Support and Engineering to resolve technical challenges and improve adoption
• Communicate customer feedback internally