Job Description

Journey with us! Combine your career goals and sense of adventure by joining our exciting team of employees. Royal Caribbean Group is pleased to offer a competitive compensation and benefits package, and excellent career development opportunities, each offering unique ways to explore the world.

We are proud to be the vacation-industry leader with global brands — including Royal Caribbean International, Celebrity Cruises and Silversea Cruises — the most innovative fleet and private destinations, and the best people. Together, we are dedicated to turning the vacation of a lifetime into a lifetime of vacations for our guests.

The Royal Caribbean Group’s AI and Analytics Team has an exciting career opportunity for a full time AI Engineer reporting to the Senior Manager, Data Science

This position is onsite and based in Miami, FL.

This position is also not eligible for work authorization sponsorship.

We are seeking a AI Engineer to build, deploy, and maintain production AI/ML and GenAI services that make enterprise AI capabilities reliable and reusable across Royal Caribbean Group. This role emphasizes AI Engineering ownership of technical foundations—platform services, MLOps/LLMOps pipelines, deployment patterns, observability, security, and architecture guardrails—so Data Science and business teams can deliver reliable AI/ML and GenAI outcomes in production. The ideal candidate combines practical engineering depth in Azure ML, Databricks, MLflow, CI/CD, Docker/Kubernetes, and GenAI patterns with clear communication, disciplined delivery, and a strong bias toward reusable enterprise capability rather than one-off prototypes.

ESSENTIAL RESPONSIBILITIES:

• AI Platform Engineering: Build and operate Azure-based AI platform components for independent AI engineering delivery, using Azure ML, Databricks, MLflow, and secure service patterns to make model deployment repeatable and supportable.
• MLOps / LLMOps: Develop CI/CD, model registry, evaluation, prompt/version control, retraining, and release workflows that help teams manage ML models and GenAI systems consistently from experimentation through production.
• Containerized Deployment: Package and deploy AI services with Docker, Kubernetes, identity controls, environment configuration, and runtime standards that improve reliability, portability, and operational readiness.
• GenAI Enablement: Implement GenAI capabilities using GPT-class models, RAG patterns, embeddings, vector databases, prompt engineering, and agent workflows where they improve reuse, quality, and enterprise scalability.
• Developer Productivity: Improve engineering productivity through reusable templates, code standards, GitHub/Azure DevOps automation, documentation, and tooling that help Data Science and AI teams ship with fewer manual steps.
• Observability: Create monitoring dashboards and alerts for latency, cost, drift, model quality, hallucination risk, token usage, and service health so production AI systems can be managed with clear operating signals.
• Architecture Guardrails: Define and apply practical guardrails for security, identity, networking, data access, model serving, and GenAI evaluation so teams can move faster without bypassing enterprise controls.
• Point Projects: Own targeted technical projects that expand independent AI engineering delivery, such as reusable deployment patterns, feature pipelines, evaluation harnesses, vector search services, or cost-optimization improvements.
• Cross-Team Collaboration: Work closely with Data Science, IT, Security, and business teams to make platform capabilities usable in real delivery contexts while maintaining clear ownership for engineering foundations and production operations.

QUALIFICATIONS / KNOWLEDGE / SKILLS:

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience building production-grade AI systems.
• Experience: Demonstrated experience appropriate to mid scope with production AI/ML or GenAI systems, including the ability to move beyond prototypes into reliable, monitored, and maintainable services.
• Cloud Infrastructure: Hands-on experience with Azure infrastructure patterns, including Azure ML, Databricks, Azure DevOps, identity, networking, secrets, compute, and deployment environments.
• MLOps: Experience with MLflow, Azure ML pipelines, model registries, feature pipelines, deployment approvals, monitoring, retraining, and model lifecycle management.
• LLMOps: Experience managing GenAI systems through prompt/version control, RAG evaluation, embeddings, vector database operations, token/cost monitoring, safety testing, and quality measurement.
• Distributed Systems: Understanding of scalable service design, asynchronous processing, failure modes, observability, and performance tuning for production AI workloads.
• Security: Knowledge of enterprise authentication, authorization, data protection, secure model serving, network boundaries, and compliance-aware deployment practices.
• Engineering: Strong Python engineering skills with modern development practices, including testing, code review, Git workflows, packaging, APIs, Docker, and CI/CD automation.
• Communication: Clear communication skills with data scientists, IT partners, and business product teams, including the ability to explain architecture decisions, delivery risks, tradeoffs, and production-readiness expectations without unnecessary jargon.

WORK ENVIRONMENT:

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of the job. The environment includes working inside and outside of an office setting, traveling to other offices, potential domestic and international travel, and working in shipboard environments. A high noise level is possible when visiting shipboard or offsite locations.

We know there’s a lot to consider. As you go through the application process, our recruiters will be glad to provide guidance and more detailed information to answer any additional questions. Thank you again for your interest in Royal Caribbean Group. We hope to see you onboard soon!

Agency and Third-Party Submissions: Please note this is a direct search by the Company, and applications through agencies and other third parties will not be accepted, nor will fees be paid for unsolicited resumes. Any unsolicited resumes will be considered the Company's property.

We know there's a lot to consider. As you go through the application process, our recruiters will be glad to provide guidance, and more relevant details to answer any additional questions. Thank you again for your interest in Royal Caribbean Group. We'll hope to see you onboard soon!

It is the policy of the Company to ensure equal employment and promotion opportunity to qualified candidates without discrimination or harassment on the basis of race, color, religion, sex, age, national origin, disability, sexual orientation, sexuality, gender identity or expression, marital status, or any other characteristic protected by law. Royal Caribbean Group and each of its subsidiaries prohibit and will not tolerate discrimination or harassment.