Staff Product Engineer, Revenue

• Demonstrated experience owning and shipping customer-facing products with Staff-level scope and impact
• Strong product judgment, customer empathy, and the ability to simplify complex problems
• Strong full-stack product engineering skills, including fluency with APIs, data models, and SQL
• Experience shipping 0→1 or early-stage products in ambiguous, fast-moving environments
• The ability to lead consequential technical decisions through sound judgment, collaboration, and influence

Desirable

• We are hiring a Staff Product Engineer to become the founding technical leader for one of Revenue.io’s most important new product investments
• You will have substantial ownership from the beginning: shaping the product with customers and company leaders, defining its technical foundation, and building the first production versions yourself
• This is a rare opportunity to take an important customer problem from an early thesis to a trusted product with meaningful market impact
• You will report directly to the Chief Engineering & AI Officer and partner closely with Product, Data, AI, and GTM leadership. This is initially a deeply hands-on individual-contributor role
• As the product succeeds, you will help establish (or manage) the team, technical standards, and operating model around it
• Work directly with Product, customers, and company leaders to identify valuable problems and turn complex requirements into intuitive workflows
• Own the technical direction and hands-on development of the product across frontend, backend, APIs, data models, and integrations
• Make foundational architecture and applied ML/AI decisions that balance rapid iteration with reliability, maintainability, and scale
• Establish a high engineering bar and lead consequential technical and product decisions through judgment, data, and influence
• Mentor cross-pod engineers and create the technical and operating foundation from which a future product team can grow
• What Success Looks Like:
• Launch a product that customers adopt and love; improve customer workflows through intuitive, high-impact features
• Validate product decisions through rapid experimentation and iterative learning cycles
• Build a system architecture and data model that support continued iteration without rework or instability