Senior Software Engineer, Commerce Platform

At Zipline, we are building the operating system for an autonomous delivery network.

The Commerce Platform team builds the commercial engine that makes that network a real business. We create the tools and integrations partners use to run their business with Zipline, the marketplace logic that connects demand to supply, and the financial infrastructure that ensures every transaction is correct and every dollar is traceable. This platform needs to scale across metros, countries, and verticals (restaurants, retail, and healthcare) handling millions of orders per day.

What you will own

You will own software across the full commercial stack, including:

• Merchant Portal - the web portal partners use to manage their Zipline business day to day
• Partner integrations - Point of Sale connectors, API integrations, and data feeds that connect merchant systems to the Zipline platform
• Marketplace Platform - internal tooling that controls how demand is prioritized, priced, and distributed across the network
• Billing Engine - the financial backbone that manages payments, commissions, settlements, and revenue flows across the marketplace
• Fulfillment apps - mobile and cloud applications for picking and loading execution at partner locations
• Customer support tooling - AI-powered support systems integrated with order, delivery, and billing infrastructure
• Serviceability & coverage tools - internal platforms for understanding and modeling where Zipline can serve customers

Hard Problems, Real Ownership

Most software roles optimize a single surface. The Commerce Platform spans consumer product, marketplace logic, partner tooling, fulfillment, and financial infrastructure.

You will work on problems like:

• How do we give merchant partners real-time operational visibility, self-serve onboarding, and financial clarity without fragmenting the system across verticals?
• How do we design marketplace policy controls that let operators safely change pricing, capacity allocation, and prioritization, with experimentation before production?
• How do we build a billing engine that traces every dollar from customer charge through partner payout across promotions, refunds, revenue shares, and multi-jurisdiction tax?
• How do we build AI-powered customer support that can actually take action, issuing refunds, applying credits, explaining delays using live mission data, rather than just surfacing information?
• How do we keep unit economics visible and margin protected as volume scales across partners, verticals, and geographies?

These systems are live and consequential. The work you do on them directly shapes the customer experience, partner success, and commercial performance of the network.

How we work

This team operates with high ownership, high trust, and a high technical bar. Engineers are expected to identify important problems, form a clear view of how the system should work, and drive solutions from concept through production.

We also expect engineers to use AI tooling effectively as a force multiplier across exploration, implementation, and debugging, while maintaining strong engineering rigor, judgment, and accountability.

What you will bring

You are likely a strong fit if you:

• have a track record of building and shipping production software across the full stack, from consumer-facing interfaces to backend services and data pipelines
• can hold both product instinct and systems judgment at the same time - you care about the user experience and the architecture that makes it reliable at scale
• understand marketplace dynamics: ordering flows, pricing logic, financial correctness, and the tradeoffs between them
• can simplify complexity, define durable abstractions, and improve the architecture around you
• thrive working across product boundaries (e.g. consumer, partner, internal tooling, and financial systems) without losing coherence
• want to shape architecture and product direction, not just implement scoped features

Our current stack includes Go, Python, React, gRPC, Kafka, PostgreSQL, AWS, Bazel, Grafana, and Honeycomb, but we value engineers who can learn new tools quickly and focus on solving the right problems.

We lean heavily into AI-assisted and agentic engineering workflows, and we're excited to work with engineers who use modern AI tooling to amplify their productivity while maintaining high standards for system design and code quality.

What Else You Need to Know