Forward Deployed AI Engineer, Real Estate and Development

About Zipline

Zipline is the world’s largest and most experienced drone delivery service. We are on a mission to serve all humans equally by ensuring access to food, medicine and 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 to date, including blood, vaccines, medical supplies, food, and retail products.

Our customers include the world’s largest and most prominent healthcare systems, governments, retailers, restaurants and global businesses who rely on us to save lives, reduce emissions, increase economic opportunity, and provide delivery from point A to point B as fast as possible. The drone is only 15% of what we’ve built to enable seamless, reliable, global operations.

Our system strengthens supply chains, reduces congestion, and gives people time back. 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 are seeking people who sculpt from first principles, enjoy facing adversity, and can do the impossible at record-breaking speeds.

Zipline is looking for Forward Deployed AI Engineers, Real Estate and Development, who will be at the forefront of bringing GenAI into one of the most complex real‐world logistics systems in the world. We operate across software, hardware, aviation, robotics, healthcare, commerce, and field operations, which means the work is practical, high‐stakes, and directly tied to production outcomes. This role is similar to being a hands‐on AI startup CTO inside Zipline: you report directly to the Head of Operations, work in a small team, own delivery of important projects, move quickly from problem discovery to shipped product, and partner directly with users.

The impact will come less from demos and more from systems that are adopted, trusted, and used in daily operations.

Forward Deployed AI Engineers work directly with Zipline teams to own GenAI strategy and implementation for high-impact operational workflows and teams. On a daily basis, you will build end-to-end AI tools, take them to production, and solve real‐world problems across aviation, logistics, fulfillment, maintenance, customer operations, and commercial teams. You will work closely with operators, engineers, product teams, and business leaders to understand user needs, define the right technical approach, and implement solutions that improve how Zipline runs.

You will also bring learnings from the field back into Zipline’s broader AI tooling, platforms, and best practices. In this deployment, you will focus on market strategy, city engagement, permitting readiness, development workflows, design coordination, lease‐to‐permit tracking, site constraints, construction handoffs, and regional execution.

• We value past experience building things that work. We do not need specific degrees; we need results. Make sure your resume highlights what you have built, shipped, automated, scaled, or made real. It matters less where, when, or for whom you built it; what matters is that it was useful, ambitious, technically strong, and cool.
• We value an engineering mindset focused on delivering production AI systems, not academic benchmarks.
• You should have experience building with LLMs, data processing pipelines, and analytics tools, and you should be comfortable decomposing messy business problems into reliable technical workflows.
• We require past experience building GenAI solutions, a strong understanding of the AI landscape, and a solid foundation in machine learning basics such as evaluation, training concepts, and problem decomposition.
• You should…