Forward Deployed AI Engineer, Launch, Design, and Construction Handoff

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.

About You & the Role

Zipline is looking for Forward Deployed AI Engineers, Launch, Design, and Construction Handoff, 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.

What You’ll Do

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 launch readiness, design coordination, service-level tracking, construction handoffs, regional readiness, partner readiness, owner and date tracking, post-launch debt, and blocker escalation.

What You’ll Bring

• 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 be a strong coder, with proficiency in Python, TypeScript/JavaScript, Java, C++, or similar languages.


• You should be comfortable collaborating with technical and non-technical teammates, working in dynamic environments, and iterating directly with users.


• Ability and interest in traveling to Zipline sites as needed is helpful up to 50% depending on the organization you’ll be deployed into.


• Experience with launch operations, construction coordination, field operations, project management systems, workflow automation, or readiness dashboards is especially helpful.

WHAT ELSE YOU NEED TO KNOW

This will be an in-office role based out of our South San Francisco HQ. Must be able to travel up to 25% of the time either to our HQ or into the Field.

The starting cash range for this role is $112,500 - $300,000; please note that this is a target, starting cash range for a candidate who meets the minimum qualifications for this role. We are always open to negotiation. 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 package for this role may also include: equity compensation; overtime pay; discretionary annual or performance bonuses; sales incentives; benefits such as medical, dental and vision insurance; paid time off; and more.

Zipline is an equal opportunity employer and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws or our own sensibilities.

We value diversity at Zipline and welcome applications from those who are traditionally underrepresented in tech. If you like the sound of this position but are not sure if you are the perfect fit, please apply!