Staff Backend Engineer, Revenue

Ovii's Interpretation of the Role

Zapier seeks a Staff Backend Engineer to own the technical vision of its Revenue Zone, shaping billing, pricing, payments and entitlement platforms. The role drives architecture, performance and reliability for finance‑grade systems while partnering across product, finance and sales.

Role Snapshot

• Technical leader for revenue platform
• Design billing & pricing architecture
• Drive performance & reliability
• Mentor engineers and raise technical standards
• Collaborate cross‑functionally with product, finance and sales
• Own revenue‑critical systems

Must-Have Requirements

• Backend systems design
• API development
• Performance optimization
• Billing & payments domain knowledge
• Pricing model architecture
• Complex production systems at scale
• Billing/payments domain experience

Nice-to-Have Signals

• AI‑assisted development tools
• Technical mentorship
• AI tool fluency

Work Setup

• Location: San Francisco, United States
• Work mode: REMOTE
• Remote scope: UNSPECIFIED
• Remote countries: United States, NAMER
• Employment type: Full-Time

Eligibility Gates

• Visa sponsorship: unknown

Not Specified in JD

• Salary range
• Visa sponsorship
• Relocation
• Travel
• Security clearance
• Coding test

What You'll Likely Work On

• Define and evolve the long‑term architecture of the Revenue Zone
• Lead high‑impact initiatives that decouple billing from account systems and enable rapid pricing experimentation
• Own and improve the reliability, observability and correctness of billing, pricing, payments, checkout and entitlement services
• Guide API design, data modeling and caching strategies for scalability and developer experience
• Partner with Pricing & Packaging, Product, Design, Finance and Sales to drive ARR growth
• Identify performance bottlenecks and deliver measurable latency and reliability improvements
• Mentor engineers, conduct code reviews and champion documentation and developer experience

Good Fit If You Have

• Fluent use of AI coding tools and clear judgment on where AI is appropriate
• Comfort navigating large, mature monoliths and finding leverage points
• Experience delivering outcomes in finance‑grade, high‑correctness systems