Principal Software Engineer - Revenue Hub

HubSpot is an AI-powered customer platform that provides software, integrations, and resources for businesses to connect marketing, sales, and service. The Principal Software Engineer will shape the technical future of Revenue Hub by building and architecting scalable CPQ, Billing, Payments, and Revenue OS systems, while defining safe and predictable APIs and platform patterns for developers and AI agents.

Responsibilities:

• Shape the technical roadmap across CPQ, Billing, and Payments with strong, opinionated patterns
• Define and evolve core domain models so pricing, products, contracts, invoices, and payments behave predictably in the UI, over the API, and inside agent-driven workflows
• Design the API and platform contracts that let developers, partners, and AI agents extend Revenue Hub without coupling to internals
• Create frameworks that make the platform easy to extend without adding complexity
• Write code regularly. Lead design reviews and build high-impact systems end-to-end
• Own large multi-team initiatives that span CPQ, Billing, and Payments
• Take prototypes to production at scale
• Set patterns for extensibility, contract boundaries, financial correctness, event-driven consistency, and how AI agents safely interact with commerce objects
• Push for simplicity where the domain wants to get complicated, and consistency where surfaces can drift
• Influence product strategy across CPQ, Buyer Portal, and Revenue OS
• Help teams make clear tradeoffs between speed, correctness, compliance, and long-term platform health
• Mentor senior engineers and tech leads
• Drive thoughtful design decisions and guide learnings from incidents and large migrations
• Help teams align on patterns that reduce complexity and increase reliability

Requirements:

• Proven experience building and scaling distributed systems with strict correctness requirements
• Strong instincts for API and platform design. You've built things external teams depend on and know what that responsibility feels like
• Background working with complex state machines, financial flows, or high-integrity data models
• Familiarity with agentic systems and what it means for AI to safely act on structured data, not just read it
• The ability to work horizontally across many teams and get alignment on platform patterns
• A habit of turning ambiguity into clear plans and working software, and staying hands-on every step of the way