Forward Deployed AI Engineer (Operations)

Role Overview Zipline is looking for Forward Deployed AI Engineers 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 Qualifications & Experience Strong coder with proficiency in Python, TypeScript/JavaScript, Java, C++, or similar languages Past experience building GenAI solutions, strong understanding of the AI landscape, and solid foundation in machine learning basics such as evaluation, training concepts, and problem decomposition Ability and interest in traveling to Zipline sites as needed up to 50% depending on the organization you’ll be deployed into Past experience building things that work – results matter more than degree; highlight what you have built, shipped, automated, scaled, or made real Comfortable collaborating with technical and non‑technical teammates, working in dynamic environments, and iterating directly with users Experience building with LLMs, data processing pipelines, and analytics tools; comfortable decomposing messy business problems into reliable technical workflows Engineering mindset focused on delivering production AI systems, not academic benchmarks #J-18808-Ljbffr Zipline