Senior Software Engineer - Maps Platform

About Zipline

Zipline is the world’s largest and most experienced autonomous delivery service, founded to serve all humans equally by ensuring access to essential goods anytime, anywhere. We design, build, and operate the world’s largest autonomous logistics system, delivering critical supplies quickly and reliably. Today, Zipline operates on four continents, makes a delivery somewhere in the world every 30 seconds, and has completed millions of deliveries including blood, vaccines, medical supplies, food, and commercial products.

Our customers include healthcare systems, governments, retailers, and global brands who rely on us to save lives, reduce emissions, increase economic opportunity, and provide new logistics services at scale.

Our technology goes beyond drones. We deploy integrated logistics infrastructure that strengthens supply chains, reduces congestion, and enables instant delivery, transforming how essential goods reach people everywhere. With more than 140 million commercial autonomous miles safely flown, Zipline is redefining access to healthcare, consumer products, and food across the globe.

We operate at a global scale and are looking for practical problem solvers who thrive on real-world challenges and rapid growth. Our team is motivated by building systems that have a direct, meaningful impact on people’s lives and by scaling the future of logistics.

We’re building the mapping infrastructure that powers every Zipline flight. Maps Platform engineers build the backbone that serves geographic data, features, and map-driven services to Zipline’s products and operators.

You’ll make map data fast, accurate, and reliable for both human workflows (map editors, operator dashboards, regulatory UIs) and autonomous systems (routing, onboard systems). This role mixes backend, data, platform engineering and user interface design with pragmatic production ownership.

• Own the foundation of flight intelligence. The systems you build directly power how aircraft understand and navigate the world.
• Massive data challenges. You’ll design pipelines that process and serve large-scale geospatial datasets with strict requirements for accuracy, consistency, and availability.
• End-to-end ownership. From raw data ingestion to production services, you’ll build systems that are critical to real-world operations.
• Cross-functional impact. Your work will be used across autonomy, routing, simulation, and operations.
• AI-accelerated engineering. We leverage modern AI and agentic workflows to increase engineering velocity while maintaining strong system rigor.

We care far more about how you approach problems than experience with any specific technology. Strong candidates typically have:

• Experience building and operating large-scale data pipelines
• A track record shipping reliable services and APIs
• Extreme ownership mindset with the ability to drive projects end-to-end
• Experience working with large datasets and designing reliable data processing logic
• Familiarity with data modeling, data quality, and validation in production systems
• Comfort working with cross-functional teams and integrating systems across domains
• Strong backend or distributed systems engineering fundamentals
• Experience with geospatial systems, mapping technologies, or GIS tooling is a plus, but not required.

Our current stack includes technologies such as Go, Python, PostgreSQL/PostGIS, Kafka, and AWS, but we value engineers who can learn quickly and focus on solving the right problems.

We also lean heavily into AI-assisted engineering workflows and are excited to work with engineers who use modern tools to amplify productivity while maintaining high standards for system design and data quality.

The starting cash range for this role is $170,000 - $210,000. Please note that this is a target, starting cash range for a candidate who meets the minimum qualifications for this role. The final cash pay for this role will depend on a variety of factors, including a specific candidate's experience, qualifications, skills, working location, and projected impact. The total compensation…