Software Engineer Ii, Backend, Tvscientific

Pinterest Pinterest · Consumer · San Francisco, CA · tvScientific

Backend Engineer II at Pinterest's tvScientific, focusing on designing, building, and scaling contract and billing systems for a CTV advertising platform. The role involves developing backend services for contract lifecycle management, supporting various billing models (CPA, CPM), and ensuring system accuracy, auditability, and reliability. It emphasizes domain modeling, data integrity, and collaboration with Product, Finance, and Data teams. The role also requires leveraging AI tools for workflow improvement while maintaining critical evaluation and ownership of AI-assisted work.

What you'd actually do

  1. Design and implement backend systems for contract lifecycle management, including creation, versioning, approvals, amendments, and renewals
  2. Build and evolve contract management capabilities (e.g., terms, payouts, attribution rules, eligibility, and partner-specific logic) for our CPA Contract/Billing model
  3. Support the expansion of CPM billing model contracts, including rate management, impression-based calculations, and integrations with billing and finance systems
  4. Develop APIs and services that serve customers, internal operations teams, and finance stakeholders
  5. Partner closely with Product, Finance, and Data teams to translate business requirements into robust technical solutions

Skills

Required

  • Experience with billing/contract mechanisms (specifically affiliate platforms)
  • Bachelor’s degree in computer science, a related field or equivalent experience
  • Experience building large-scale full-stack products.
  • Deep understanding of web development and best practices in React/Redux
  • Strong experience with programming languages Javascript and Python/Java
  • Strong software engineering principles and practices
  • Strong collaboration and communication skills
  • Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
  • Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review)
  • High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables

Nice to have

  • Experience working closely with finance or accounting teams
  • Background in building audit-friendly or compliance-sensitive systems

What the JD emphasized

  • strong guarantees around correctness, auditability, and operational reliability
  • clear domain modeling, data integrity, and sound engineering judgment matter more than any specific implementation approach
  • Ensure systems are auditable, accurate, and compliant, with strong data integrity guarantees
  • High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables