AI Forward Deployed Engineer

One of the best-known names in cruising, Princess is the world’s leading international premium cruise line and tour company, carrying millions of guests each year to hundreds of destinations around the globe.  We give our guests the Medallion Class experience others simply can’t. The Love Boat promises something for everyone. 

We are looking to hire a Principal AI Forward Deployed Engineer.  The Principal AI Forward Deployed Engineer is embedded directly with business units across the organization to quickly prototype, deploy, customize, and operationalize AI solutions that solve critical business problems. This role bridges the gap between the AI/Data team and the business—translating ambiguous challenges into working AI applications that deliver measurable value.

This is a full-stack engineering role with deep backend expertise. You will design and build production-grade applications, APIs, and data pipelines that bring AI capabilities to life. Proficiency in modern application development, containerization, orchestration, and event-driven architectures is essential.

Unlike traditional engineering roles, the Principal AI Forward Deployed Engineer operates at the intersection of technical execution and business problem-solving. You will work side-by-side with stakeholders in Guest Services, Revenue Management, Operations, Food & Beverage, and other functions to rapidly prototype, deploy, and iterate on AI solutions in real-world environments—including shipboard systems.

This role requires a builder's mindset: someone who can scope a vague problem, architect a robust solution, write production-grade code, and ship it fast. You will bring field insights back to the core AI team, identifying reusable patterns and influencing the product roadmap based on what you learn in the field.

Here’s a summary of what Princess is looking for in a Principal AI Forward Deployed Engineer.  Is this you? 

Responsibilities: 

• AI Application Development & Deployment:  Architect, build, and deploy enterprise-grade AI-powered applications using modern backend technologies (Python, Node.js, FastAPI, Express). Design and implement robust APIs and microservices architectures that integrate AI/ML models—including LLMs and agentic systems—with business systems at scale. Lead containerization strategies using Docker and manage complex deployments via Kubernetes (EKS/ECS) with a focus on reliability, scalability, and performance. Design and implement event-driven architectures using Kafka or similar streaming platforms for real-time data processing and AI inference. Take full ownership of end-to-end delivery from technical scoping and architecture design through production deployment, monitoring, optimization, and ongoing operational excellence.