Staff Engineer, Usage Based Billing

Stripe is a financial infrastructure platform for businesses, and they are seeking a Staff Backend Engineer to guide their Usage-Based Billing product to General Availability. The role involves architecting high-throughput metering systems, improving product stability, and mentoring senior engineers while ensuring a straightforward developer experience for users.

Responsibilities:

• Lead technical initiatives to move Usage-Based Billing from a high-touch pilot phase to a robust, General Availability product. You will identify improvements that influence core product stability
• Embed with engineering teams at major AI companies to build high-leverage capabilities. You will solve their immediate scaling issues and translate those fixes into long-term product features
• Design high-throughput ingestion systems for high cardinality data. The backend must handle the massive usage spikes common in GenAI models
• Develop customization frameworks and public APIs. As we scale, interfaces must remain usable for developers building complex financial workflows
• Translate ambiguous user needs into technical solutions. You will provide feedback to core product teams to shape the future of Stripe’s Revenue & Financial Automation offerings
• Mentor senior engineers and improve engineering standards and tooling within the team

Requirements:

• 10+ years of experience in software development roles
• A mix of backend experience (scaling, concurrency, distributed data) and product instincts (API design, user empathy, workflow definition)
• Experience working in complex distributed systems with significant scale ('billions of events')
• Comfortable working directly with external engineering teams. You can communicate complex technical topics clearly
• Proficiency in at least one modern programming language (e.g., Java, Ruby, Python) and experience with big data technologies (e.g., Kafka, Flink)
• Experience as a technical lead defining roadmaps for complex projects that span multiple teams
• Experience launching a complex technical product to General Availability (GA)
• Experience building and operating high-scale, real-time data processing systems
• Familiarity with the specific growth patterns and technical needs of AI companies
• Track record of evolving internal platforms into public-facing products